{"as_of":"2026-08-08T11:09:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8a8897595e4a7c09f72015d9452620c56d92c42b3915baec0590be09799c2715","coverage":[{"denominator":37,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":37,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T10:43:07.468962Z","state":"measured"},{"denominator":42,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":42,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T16:42:40.840354Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-04T07:59:39.936905Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.04831","snapshot_observed_at":"2026-08-06T16:42:40.840354Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.12774","last_updated":"2025-07-17T04:31:55Z","snapshot_observed_at":"2026-08-08T03:04:37.730389Z","submitted_at":"2025-07-17T04:31:55Z","title":"A Comprehensive Survey of Electronic Health Record Modeling: From Deep Learning Approaches to Large Language Models","version":1},"reference_index":221,"source":"pdf_text","source_observed_at":"2026-08-06T16:42:40.840354Z"},"links":{"cited_paper":"/paper/2506.04831","citing_paper":"/paper/2507.12774"},"observation_digest":"sha256:5bf08098942cc1b4a886a3d4dcf8d0287ec14d3069743e34f27ede694b3e5488","observation_id":"348a3473-8b1c-4366-8487-6a1e4194eadb","resolution":{"observed_at":"2026-08-06T16:42:40.840354Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"cited_work":{"arxiv_id":"2506.04831","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.04831","snapshot_observed_at":"2026-08-04T02:23:04.332198Z","title":"From ehrs to patient pathways: Scalable modeling of longitudinal health trajectories with llms","venue":null,"work_id":"67dfefa6-7e1c-45ea-a183-ca1de598d876","year":2026},"citing_paper":{"arxiv_id":"2604.18570","last_updated":"2026-04-21T21:55:35Z","snapshot_observed_at":"2026-08-02T08:50:19.349001Z","submitted_at":"2026-04-20T17:55:47Z","title":"A multimodal and temporal foundation model for virtual patient representations at healthcare system scale","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-10T05:03:40.305624Z"},"links":{"cited_paper":"/paper/2506.04831","citing_paper":"/paper/2604.18570"},"observation_digest":"sha256:6bc0d5af29312e24d99dcd372c24bc792ad08615d9b21a6ff8ab919d1c536b9d","observation_id":"19418c34-731f-4b95-9c78-b9fd3487e69e","resolution":{"observed_at":"2026-08-04T02:23:04.332198Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"cited_work":{"arxiv_id":"2506.04831","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.04831","snapshot_observed_at":"2026-08-04T02:23:04.332198Z","title":"From ehrs to patient pathways: Scalable modeling of longitudinal health trajectories with llms","venue":null,"work_id":"67dfefa6-7e1c-45ea-a183-ca1de598d876","year":2026},"citing_paper":{"arxiv_id":"2605.12335","last_updated":"2026-05-12T16:17:03Z","snapshot_observed_at":"2026-07-06T23:24:03.984179Z","submitted_at":"2026-05-12T16:17:03Z","title":"EHR-RAGp: Retrieval-Augmented Prototype-Guided Foundation Model for Electronic Health Records","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-13T03:17:13.143208Z"},"links":{"cited_paper":"/paper/2506.04831","citing_paper":"/paper/2605.12335"},"observation_digest":"sha256:5323fad08644bc037938deeed155451b75526c225ebc24b432fc01feeeae2ea7","observation_id":"84473f2b-14d9-4d7f-8323-f92a32777b27","resolution":{"observed_at":"2026-08-04T02:23:04.332198Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"cited_work":{"arxiv_id":"2506.04831","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.04831","snapshot_observed_at":"2026-08-04T02:23:04.332198Z","title":"From ehrs to patient pathways: Scalable modeling of longitudinal health trajectories with llms","venue":null,"work_id":"67dfefa6-7e1c-45ea-a183-ca1de598d876","year":2026},"citing_paper":{"arxiv_id":"2606.02812","last_updated":"2026-06-01T19:30:07Z","snapshot_observed_at":"2026-07-06T23:43:07.940839Z","submitted_at":"2026-06-01T19:30:07Z","title":"Traj-Evolve: A Self-Evolving Multi-Agent System for Patient Trajectory Modeling in Lung Cancer Early Detection","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-06-28T14:20:06.381334Z"},"links":{"cited_paper":"/paper/2506.04831","citing_paper":"/paper/2606.02812"},"observation_digest":"sha256:41b71add9497576a4154358877b60b5e6d7ceb97ec7c2284c797e74d5f82d287","observation_id":"49c54621-187e-4184-821e-1d14d33774c4","resolution":{"observed_at":"2026-08-04T02:23:04.332198Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"cited_work":{"arxiv_id":"2506.04831","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.04831","snapshot_observed_at":"2026-08-04T02:23:04.332198Z","title":"From ehrs to patient pathways: Scalable modeling of longitudinal health trajectories with llms","venue":null,"work_id":"67dfefa6-7e1c-45ea-a183-ca1de598d876","year":2026},"citing_paper":{"arxiv_id":"2606.22101","last_updated":"2026-06-20T15:34:26Z","snapshot_observed_at":"2026-08-07T08:01:25.585886Z","submitted_at":"2026-06-20T15:34:26Z","title":"OphthaDT: Generative Digital Twins for Forecasting Visual Acuity Trajectories in Ophthalmology","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-06-26T12:25:49.005706Z"},"links":{"cited_paper":"/paper/2506.04831","citing_paper":"/paper/2606.22101"},"observation_digest":"sha256:a61160b69321a54cdf575f995678ed4acff21986bba2b871c0ef983c17485e7f","observation_id":"991bc753-6a27-47df-a147-03cf1d676174","resolution":{"observed_at":"2026-08-04T02:23:04.332198Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2506.04831/citation-record","integrity":"/paper/2506.04831/integrity","json":"/paper/2506.04831/citation-record.json","paper":"/paper/2506.04831"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.852217Z","title":"Unsloth, 2023","venue":null,"work_id":"98274140-0f8b-441c-801a-4eebc3a76a29","year":2023},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.335162Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:c2557d5645065b9369901cab00b3826d56f57a6e83a807124da97a87c476934c","observation_id":"31f33ba6-73b8-486c-912a-55d8540cbcfc","resolution":{"observed_at":"2026-08-07T10:43:07.856104Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.842053Z","title":"Snomed ct standard ontology based on the ontology for general medical science","venue":null,"work_id":"4137666a-2125-41fd-9b11-ac1b88f54ac3","year":2018},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.340098Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:7dccf68ab67244f4f9b7dc30a9462f5d2961e8e728b419555cf4ada367bfe0e3","observation_id":"da9b4ccf-c3ef-4aca-92f0-5f1c9f723209","resolution":{"observed_at":"2026-08-07T10:43:07.845616Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.14567","last_updated":"2024-11-15T00:24:00Z","snapshot_observed_at":"2026-07-06T18:18:39.093732Z","submitted_at":"2024-05-23T13:43:29Z","title":"EHRMamba: Towards Generalizable and Scalable Foundation Models for Electronic Health Records","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.14567","snapshot_observed_at":"2026-08-07T10:43:07.343695Z","title":"Ehrmamba: Towards generalizable and scalable foundation models for electronic health records","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.343695Z"},"links":{"cited_paper":"/paper/2405.14567","citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:f12425bc3705ef93d46750e16e5cdc461643a568a80ae177df4c7151df3d7912","observation_id":"3df6d2b8-8018-4cfe-9260-2794b0b18a88","resolution":{"observed_at":"2026-08-07T10:43:07.343695Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.348278Z","title":"Physiobank, physiotoolkit, and physionet: components of a new research resource for complex physiologic signals","venue":null,"work_id":null,"year":2000},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.348278Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:ab85d0ec61662cf8f53d1be1d25d9c8d605816d1647708753380df9eb810ee41","observation_id":"3de89174-b2e9-4e85-b75c-d0351e3047ed","resolution":{"observed_at":"2026-08-07T10:43:07.348278Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.351976Z","title":"Lo RA : Low-rank adaptation of large language models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.351976Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:e7f60a3aa8f0c586f30dc852c1dcdd9f08486ecee508830bc247b34568adf8a0","observation_id":"4568f5a6-390c-4509-8a65-15e1f91890a3","resolution":{"observed_at":"2026-08-07T10:43:07.351976Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.08082","last_updated":"2024-09-01T05:03:16Z","snapshot_observed_at":"2026-07-06T14:18:30.314936Z","submitted_at":"2022-11-15T12:05:03Z","title":"UniHPF : Universal Healthcare Predictive Framework with Zero Domain Knowledge","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.08082","snapshot_observed_at":"2026-08-07T10:43:07.355662Z","title":"Unihpf: Universal healthcare predictive framework with zero domain knowledge","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.355662Z"},"links":{"cited_paper":"/paper/2211.08082","citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:f076738bba04713055d3b846561fce49d434f13a8f03739b34221096334cf579","observation_id":"637ffca6-2add-46f6-98a2-87f6c2ff596e","resolution":{"observed_at":"2026-08-07T10:43:07.355662Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.819033Z","title":"Genhpf: General healthcare predictive framework for multi-task multi-source learning","venue":null,"work_id":"3c6091f1-c770-4488-9abd-61410067d673","year":2023},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.359612Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:f24239a2dce8e5f4621ba30c49600e78fb892454c09aca5bf9b423359bd7370b","observation_id":"c72e2b7a-3bdf-49f1-b69a-7b7985130092","resolution":{"observed_at":"2026-08-07T10:43:07.822623Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.808685Z","title":"Mimic-iv (version 2.2)","venue":null,"work_id":"070d6834-2e6e-4e6f-8739-3b2b3a4d67db","year":2023},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.362836Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:b39eded4e7f31d2e92aff69f8a9b058173499517ecba291849bd78384e10b3d6","observation_id":"816a8dbb-5bf3-44c4-8989-829a0103e3c4","resolution":{"observed_at":"2026-08-07T10:43:07.812438Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.798727Z","title":"Mimic-iv-ed","venue":null,"work_id":"e3904e12-581e-40e7-90ee-ac37e578fbff","year":2021},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.366865Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:307fb7d7a0358fb2b5835df2f3197b65e7c524cb1f0cd464c020f7257ca439ab","observation_id":"65782a8a-b3cf-41b3-9e4b-a06fa0293d50","resolution":{"observed_at":"2026-08-07T10:43:07.802058Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.788610Z","title":"Mimic-iv, a freely accessible electronic health record dataset","venue":null,"work_id":"711c92ba-7bf3-429a-b42b-3ca4444232c6","year":2023},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.370898Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:ab3492e23f9cb63e7f98b7fafa40038a296ebc4d4f9ef307ddf68cfc4635722a","observation_id":"81fcf2b5-0387-4e1a-9350-a7fd4e2645c0","resolution":{"observed_at":"2026-08-07T10:43:07.792349Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.778496Z","title":"General-purpose retrieval-enhanced medical prediction model using near-infinite history","venue":null,"work_id":"d2d08b70-737e-4a9c-8e6d-fe4c5a99e834","year":2024},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.374366Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:4edd03214f97e916448cdfaf10c65d8f9036e94a6cc9d2f226aaf4c07d34dea4","observation_id":"7249b211-b27a-45fa-a4e9-8a13c2d2aced","resolution":{"observed_at":"2026-08-07T10:43:07.782177Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.766933Z","title":"Foresight—a generative pretrained transformer for modelling of patient timelines using electronic health records: a retrospective modelling study","venue":null,"work_id":"b2eeb953-69a3-4f1d-8c2e-c5f2ec9855d4","year":2024},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.378176Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:ae17ecf94f8468ffdd143f141df8dfcec56dfa7fca06963409bdf918fd7940f3","observation_id":"3dbdce46-cf82-4f8a-8df6-6fddfa1aa926","resolution":{"observed_at":"2026-08-07T10:43:07.770700Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.00160","last_updated":"2024-04-29T21:37:34Z","snapshot_observed_at":"2026-08-05T01:34:45.671455Z","submitted_at":"2024-01-31T20:31:56Z","title":"Emergency Department Decision Support using Clinical Pseudo-notes","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.00160","snapshot_observed_at":"2026-08-07T10:43:07.381552Z","title":"Emergency department decision support using clinical pseudo-notes","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.381552Z"},"links":{"cited_paper":"/paper/2402.00160","citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:3eb16fb1ff4e8b87bba7091f3ae4546e25abbd768d7911eb71339d709c75c014","observation_id":"edf82feb-87e0-45d8-8ea8-8f745e348c16","resolution":{"observed_at":"2026-08-07T10:43:07.381552Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.756897Z","title":"Behrt: transformer for electronic health records","venue":null,"work_id":"722a75d2-b3bf-4d7b-a535-4f9d964e4176","year":2020},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.385296Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:a70d95bdfba477bc227092e0231ee057f185c9c6f63cdc525e1e6c08ef4bbe72","observation_id":"226ea0c1-9f66-4994-9efd-49840631a800","resolution":{"observed_at":"2026-08-07T10:43:07.760385Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.746991Z","title":"Hi-behrt: hierarchical transformer-based model for accurate prediction of clinical events using multimodal longitudinal electronic health records","venue":null,"work_id":"fc747665-263b-4ee6-85b0-e918da7fb9ad","year":2022},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.388706Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:a1528d57aa5b7f56c9a807e673c1183f00e153c9fb91b48c451a5e41589011fc","observation_id":"8664168e-678f-4e89-b80b-d340aad74367","resolution":{"observed_at":"2026-08-07T10:43:07.750656Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.737366Z","title":"Revisiting the mimic-iv benchmark: Experiments using language models for electronic health records","venue":null,"work_id":"cb27453b-b063-4bb4-b5f1-d8f902afbc95","year":2024},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.392094Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:8df73213e28cb19c4f536bc1049b4dc0ea659cd5951bf9a2963e0085652dbd83","observation_id":"9f769901-c51a-4c6f-bc46-8f93261dda58","resolution":{"observed_at":"2026-08-07T10:43:07.740861Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.726684Z","title":"Large language models forecast patient health trajectories enabling digital twins","venue":null,"work_id":"9666db52-799f-4c32-921e-7bb6469e8dac","year":2025},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.395420Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:0c99a5f1d4b1580a0425d53508b6e1e26544828b48a3361e91beb3e1bdf599fd","observation_id":"7251cfcb-4f01-4b8a-aa6b-59a27842ca3a","resolution":{"observed_at":"2026-08-07T10:43:07.730259Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.716045Z","title":"A comprehensive ehr timeseries pre-training benchmark","venue":null,"work_id":"76faf818-9c0a-4afb-920b-d8d44c2f5969","year":2021},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.398669Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:2865b8e587d5eb868938da10afce608d4858f90dc57315e78c8fa382e0d73e5c","observation_id":"8123ef4b-4fee-482f-86f4-625d6db6cbac","resolution":{"observed_at":"2026-08-07T10:43:07.719609Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.705780Z","title":"Event stream gpt: a data pre-processing and modeling library for generative, pre-trained transformers over continuous-time sequences of complex events","venue":null,"work_id":"2778a5ca-590b-4c5f-b1ba-5f9dcdf499a4","year":2023},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.402804Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:afac3d46313f1c38816240a86cbe5fd8ac6cfa771ac850ff126d24083eaa8e0c","observation_id":"8b015592-34c7-49c2-b46f-36d00915faae","resolution":{"observed_at":"2026-08-07T10:43:07.709450Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.695514Z","title":"Cehr-bert: Incorporating temporal information from structured ehr data to improve prediction tasks","venue":null,"work_id":"941a80e6-b983-40e6-ac31-3cd43682b156","year":2021},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.406417Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:f604095c8c78c65a6f17ce36c549633bb3cd86d3cb1f397d680c5f1fb0a55cb5","observation_id":"e5090340-03b9-4a48-9b23-788f8d82755b","resolution":{"observed_at":"2026-08-07T10:43:07.699096Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.04400","last_updated":"2024-05-06T01:10:56Z","snapshot_observed_at":"2026-08-05T00:15:41.802392Z","submitted_at":"2024-02-06T20:58:36Z","title":"CEHR-GPT: Generating Electronic Health Records with Chronological Patient Timelines","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.04400","snapshot_observed_at":"2026-08-07T10:43:07.409978Z","title":"Cehr-gpt: Generating electronic health records with chronological patient timelines","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.409978Z"},"links":{"cited_paper":"/paper/2402.04400","citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:e730e5baba11b589babafa101d73e3a242cd36e2424f2d79091b3d20adba50b8","observation_id":"b0c4495c-dd2a-4c6e-8863-1c6bd951cd3b","resolution":{"observed_at":"2026-08-07T10:43:07.409978Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.683945Z","title":"Unsupervised pre-training of graph transformers on patient population graphs","venue":null,"work_id":"e19a635d-85a5-42ed-b20a-77a2124e57ec","year":2023},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.414441Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:e716d05eabfc03f1460d8528a6a89ac6b974ab11387a606d194a2e47a61907a1","observation_id":"ee216f72-493d-4298-b8ba-e98216761651","resolution":{"observed_at":"2026-08-07T10:43:07.687768Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.672956Z","title":"Med-bert: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction","venue":null,"work_id":"1dc807bb-96d1-4c97-9cdd-9dd28194c3b9","year":2021},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.417998Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:e9093347ea5ed07770de370596dd8485610767938961f79dc40e56b5f6497444","observation_id":"faacc7f9-f33d-4ea9-9f46-000e4612df5b","resolution":{"observed_at":"2026-08-07T10:43:07.676800Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.661950Z","title":"Zero shot health trajectory prediction using transformer","venue":null,"work_id":"158def41-2701-429b-bdd1-8c1b0325954f","year":2024},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.421374Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:95bba9244b53784552a569ee03386ce170f2fbb131c8badba7f7d16b355910b7","observation_id":"6ff53d2c-4f6c-4d99-ab56-e3bad6107a36","resolution":{"observed_at":"2026-08-07T10:43:07.665907Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.650944Z","title":"Understanding patient pathways in the context of integrated health care services-implications from a scoping review","venue":null,"work_id":"0d2a04eb-c063-4875-88df-b837402ccc53","year":2019},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.424628Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:35f7a137e134e517cccef781a4b6efe0c4a19d848149bcef71b785e52295a9e1","observation_id":"8d993909-8edd-429c-ba8a-8e8a58a12361","resolution":{"observed_at":"2026-08-07T10:43:07.654681Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.639678Z","title":"The international classification of diseases: ninth revision (icd-9), 1978","venue":null,"work_id":"377de012-1042-4fc5-bb9f-f26347014694","year":1978},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.427982Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:3fde1d3350d030d55171b731c35ee4cbc7301638648645bf9ac44c76fa13e264","observation_id":"cc2d1a00-6a5c-402d-9c44-b54f23d6e166","resolution":{"observed_at":"2026-08-07T10:43:07.643319Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.03150","last_updated":"2023-12-05T00:24:44Z","snapshot_observed_at":"2026-08-07T08:53:12.764078Z","submitted_at":"2023-01-09T02:42:39Z","title":"MOTOR: A Time-To-Event Foundation Model For Structured Medical Records","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.03150","snapshot_observed_at":"2026-08-07T10:43:07.431943Z","title":"Motor: A time-to-event foundation model for structured medical records","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.431943Z"},"links":{"cited_paper":"/paper/2301.03150","citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:f3ba25f8296b042a815d13a5b7171ed01c1d7b537b10b225ab1e324284478216","observation_id":"bda0ffb1-fc22-484f-826e-ebc78baf5817","resolution":{"observed_at":"2026-08-07T10:43:07.431943Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.629328Z","title":"Pereira, and William Bialek","venue":null,"work_id":"64f5e6fc-3baf-4392-ab4d-0ad04fc3813e","year":1999},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.436258Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:1d2d614bb5799107927ad9f04cea7520a3b6c482922f7f681bc0dd25012f92be","observation_id":"ad5c40e5-b720-4d21-82ff-9f0ae2dc02bf","resolution":{"observed_at":"2026-08-07T10:43:07.632793Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.440017Z","title":"Attention is all you need","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.440017Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:eb4aac38231a08d1d0f3cef72e0f189f47d27c4a3068c0e4409656444cc4f68b","observation_id":"4d94e5e7-7337-4b82-a2fe-52b3878354c3","resolution":{"observed_at":"2026-08-07T10:43:07.440017Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.612723Z","title":"Mimic-extract: A data extraction, preprocessing, and representation pipeline for mimic-iii","venue":null,"work_id":"94463f11-4e05-4b72-bee6-9637710a24cb","year":2020},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.443790Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:2326b71474809ae537e248c1d68bce231c4a34a4faafb60ee0ddbc4d9fab1034","observation_id":"22adc4e7-de31-4706-8853-f2d2b6b9e528","resolution":{"observed_at":"2026-08-07T10:43:07.616306Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.601491Z","title":"Ehrshot: An ehr benchmark for few-shot evaluation of foundation models","venue":null,"work_id":"fdcbbc1a-7d55-425f-ac6f-72fc21d724c6","year":2023},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.447111Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:812356840b8531ca9940f0618b3b4adad11f1cf7ef3180d0298ae2f89bfc2223","observation_id":"90e199b4-9d67-4f38-bc98-9974fc6afe81","resolution":{"observed_at":"2026-08-07T10:43:07.605120Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16178","last_updated":"2025-03-18T18:04:32Z","snapshot_observed_at":"2026-08-03T01:56:47.537884Z","submitted_at":"2024-12-09T21:58:27Z","title":"Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHRs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.16178","snapshot_observed_at":"2026-08-07T10:43:07.450438Z","title":"Context clues: Evaluating long context models for clinical prediction tasks on ehrs","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.450438Z"},"links":{"cited_paper":"/paper/2412.16178","citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:fe65d97a6203013133d24d4b62763a96056ff4ecd5ab21b177bc654ba5d8b20b","observation_id":"140c1bc3-3c94-4299-aa26-29a8139d85d0","resolution":{"observed_at":"2026-08-07T10:43:07.450438Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.10671","last_updated":"2024-09-10T13:25:53Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-07-15T12:35:42Z","title":"Qwen2 Technical Report","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.10671","snapshot_observed_at":"2026-08-07T10:43:07.454178Z","title":"Qwen2 technical report","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.454178Z"},"links":{"cited_paper":"/paper/2407.10671","citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:c67a3dae977bc81a33683dbaa0174a4b8a75ba0b7c278ed560ea2a03965bf2de","observation_id":"e31e1e98-af17-49c0-89ee-1a7e04b49570","resolution":{"observed_at":"2026-08-07T10:43:07.454178Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.587710Z","title":"A large language model for electronic health records","venue":null,"work_id":"fcc24100-975f-4552-88ff-b4122e87f42a","year":2022},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.458185Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:38b5ff1026f9576e64e273b42a2c548856ff81ec903d16bf748619dd3134ec89","observation_id":"ca301dd1-60d6-4fde-85d9-b2fa83ffe0ae","resolution":{"observed_at":"2026-08-07T10:43:07.593288Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.461797Z","title":"Transformehr: transformer-based encoder-decoder generative model to enhance prediction of disease outcomes using electronic health records","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.461797Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:5d050e441652955f94caec449a1ea2f5b25ef77b920d75c56e2f2e4c255d97d8","observation_id":"c22be0b3-f03b-4611-82ea-c533712cfaa5","resolution":{"observed_at":"2026-08-07T10:43:07.461797Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.00036","last_updated":"2025-02-26T13:18:09Z","snapshot_observed_at":"2026-08-02T02:27:29.658076Z","submitted_at":"2024-05-27T10:53:15Z","title":"EMERGE: Enhancing Multimodal Electronic Health Records Predictive Modeling with Retrieval-Augmented Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.00036","snapshot_observed_at":"2026-08-07T10:43:07.465363Z","title":"Emerge: Integrating rag for improved multimodal ehr predictive modeling","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.465363Z"},"links":{"cited_paper":"/paper/2406.00036","citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:0be418fafb452e3c9d273ed554fdb545e194c5b8db93fdfa2c2e63a18daf070a","observation_id":"2ac36d82-2aea-44a3-b8ed-0370ed4bec60","resolution":{"observed_at":"2026-08-07T10:43:07.465363Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:43:07.468962Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records","version":3},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-07T10:43:07.468962Z"},"links":{"citing_paper":"/paper/2506.04831"},"observation_digest":"sha256:4f785bd265f9c51edc14f9f8ec5237c7adb51b9cda1b2fb412da956a7fdee1ab","observation_id":"a1e0f273-70ad-4adc-97ed-bdf2083925e0","resolution":{"observed_at":"2026-08-07T10:43:07.468962Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.04831","last_updated":"2026-08-02T11:13:20Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T10:30:13.024925Z","submitted_at":"2025-06-05T09:54:01Z","title":"EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records"},"reference_resolution":{"displayed":37,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":13,"verified_exact":0,"verified_fuzzy":24},"total_outbound_references":37},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 5 inbound Pith citation observations for arXiv:2506.04831."}