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Paper Citation Record · LEDGER

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records

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.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.04831 v3

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:43:07.468962Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:42:40.840354Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-04T07:59:39.936905Z

Reference resolution

37 of 37 outbound references displayed

  • verified exact0
  • verified fuzzy24
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 31f33ba6-73b8-486c-912a-55d8540cbcfc · outbound

This paper cites Unsloth, 2023.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Unsloth, 2023

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.856104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.335162Z digest=sha256:c2557d5645065b9369901cab00b3826d56f57a6e83a807124da97a87c476934c

Observation da9b4ccf-c3ef-4aca-92f0-5f1c9f723209 · outbound

This paper cites Snomed ct standard ontology based on the ontology for general medical science.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Snomed ct standard ontology based on the ontology for general medical science

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.845616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.340098Z digest=sha256:7dccf68ab67244f4f9b7dc30a9462f5d2961e8e728b419555cf4ada367bfe0e3

Observation 3df6d2b8-8018-4cfe-9260-2794b0b18a88 · outbound

This paper cites EHRMamba: Towards Generalizable and Scalable Foundation Models for Electronic Health Records.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records EHRMamba: Towards Generalizable and Scalable Foundation Models for Electronic Health Records

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T10:43:07.343695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:43:07.343695Z digest=sha256:f12425bc3705ef93d46750e16e5cdc461643a568a80ae177df4c7151df3d7912

Observation 3de89174-b2e9-4e85-b75c-d0351e3047ed · outbound

This paper cites Physiobank, physiotoolkit, and physionet: components of a new research resource for complex physiologic signals.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Physiobank, physiotoolkit, and physionet: components of a new research resource for complex physiologic signals

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T10:43:07.348278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:43:07.348278Z digest=sha256:ab85d0ec61662cf8f53d1be1d25d9c8d605816d1647708753380df9eb810ee41

Observation 4568f5a6-390c-4509-8a65-15e1f91890a3 · outbound

This paper cites Lo RA : Low-rank adaptation of large language models.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Lo RA : Low-rank adaptation of large language models

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T10:43:07.351976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:43:07.351976Z digest=sha256:e7f60a3aa8f0c586f30dc852c1dcdd9f08486ecee508830bc247b34568adf8a0

Observation 637ffca6-2add-46f6-98a2-87f6c2ff596e · outbound

This paper cites UniHPF : Universal Healthcare Predictive Framework with Zero Domain Knowledge.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records UniHPF : Universal Healthcare Predictive Framework with Zero Domain Knowledge

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T10:43:07.355662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:43:07.355662Z digest=sha256:f076738bba04713055d3b846561fce49d434f13a8f03739b34221096334cf579

Observation c72e2b7a-3bdf-49f1-b69a-7b7985130092 · outbound

This paper cites Genhpf: General healthcare predictive framework for multi-task multi-source learning.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Genhpf: General healthcare predictive framework for multi-task multi-source learning

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.822623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.359612Z digest=sha256:f24239a2dce8e5f4621ba30c49600e78fb892454c09aca5bf9b423359bd7370b

Observation 816a8dbb-5bf3-44c4-8989-829a0103e3c4 · outbound

This paper cites Mimic-iv (version 2.2).

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Mimic-iv (version 2.2)

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.812438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.362836Z digest=sha256:b39eded4e7f31d2e92aff69f8a9b058173499517ecba291849bd78384e10b3d6

Observation 65782a8a-b3cf-41b3-9e4b-a06fa0293d50 · outbound

This paper cites Mimic-iv-ed.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Mimic-iv-ed

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.802058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.366865Z digest=sha256:307fb7d7a0358fb2b5835df2f3197b65e7c524cb1f0cd464c020f7257ca439ab

Observation 81fcf2b5-0387-4e1a-9350-a7fd4e2645c0 · outbound

This paper cites Mimic-iv, a freely accessible electronic health record dataset.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Mimic-iv, a freely accessible electronic health record dataset

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.792349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.370898Z digest=sha256:ab3492e23f9cb63e7f98b7fafa40038a296ebc4d4f9ef307ddf68cfc4635722a

Observation 7249b211-b27a-45fa-a4e9-8a13c2d2aced · outbound

This paper cites General-purpose retrieval-enhanced medical prediction model using near-infinite history.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records General-purpose retrieval-enhanced medical prediction model using near-infinite history

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.782177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.374366Z digest=sha256:4edd03214f97e916448cdfaf10c65d8f9036e94a6cc9d2f226aaf4c07d34dea4

Observation 3dbdce46-cf82-4f8a-8df6-6fddfa1aa926 · outbound

This paper cites Foresight—a generative pretrained transformer for modelling of patient timelines using electronic health records: a retrospective modelling study.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Foresight—a generative pretrained transformer for modelling of patient timelines using electronic health records: a retrospective modelling study

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.770700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.378176Z digest=sha256:ae17ecf94f8468ffdd143f141df8dfcec56dfa7fca06963409bdf918fd7940f3

Observation edf82feb-87e0-45d8-8ea8-8f745e348c16 · outbound

This paper cites Emergency Department Decision Support using Clinical Pseudo-notes.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Emergency Department Decision Support using Clinical Pseudo-notes

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T10:43:07.381552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:43:07.381552Z digest=sha256:3eb16fb1ff4e8b87bba7091f3ae4546e25abbd768d7911eb71339d709c75c014

Observation 226ea0c1-9f66-4994-9efd-49840631a800 · outbound

This paper cites Behrt: transformer for electronic health records.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Behrt: transformer for electronic health records

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.760385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.385296Z digest=sha256:a70d95bdfba477bc227092e0231ee057f185c9c6f63cdc525e1e6c08ef4bbe72

Observation 8664168e-678f-4e89-b80b-d340aad74367 · outbound

This paper cites Hi-behrt: hierarchical transformer-based model for accurate prediction of clinical events using multimodal longitudinal electronic health records.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Hi-behrt: hierarchical transformer-based model for accurate prediction of clinical events using multimodal longitudinal electronic health records

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.750656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.388706Z digest=sha256:a1528d57aa5b7f56c9a807e673c1183f00e153c9fb91b48c451a5e41589011fc

Observation 9f769901-c51a-4c6f-bc46-8f93261dda58 · outbound

This paper cites Revisiting the mimic-iv benchmark: Experiments using language models for electronic health records.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Revisiting the mimic-iv benchmark: Experiments using language models for electronic health records

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.740861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.392094Z digest=sha256:8df73213e28cb19c4f536bc1049b4dc0ea659cd5951bf9a2963e0085652dbd83

Observation 7251cfcb-4f01-4b8a-aa6b-59a27842ca3a · outbound

This paper cites Large language models forecast patient health trajectories enabling digital twins.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Large language models forecast patient health trajectories enabling digital twins

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.730259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.395420Z digest=sha256:0c99a5f1d4b1580a0425d53508b6e1e26544828b48a3361e91beb3e1bdf599fd

Observation 8123ef4b-4fee-482f-86f4-625d6db6cbac · outbound

This paper cites A comprehensive ehr timeseries pre-training benchmark.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records A comprehensive ehr timeseries pre-training benchmark

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.719609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.398669Z digest=sha256:2865b8e587d5eb868938da10afce608d4858f90dc57315e78c8fa382e0d73e5c

Observation 8b015592-34c7-49c2-b46f-36d00915faae · outbound

This paper cites Event stream gpt: a data pre-processing and modeling library for generative, pre-trained transformers over continuous-time sequences of complex events.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Event stream gpt: a data pre-processing and modeling library for generative, pre-trained transformers over continuous-time sequences of complex events

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.709450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.402804Z digest=sha256:afac3d46313f1c38816240a86cbe5fd8ac6cfa771ac850ff126d24083eaa8e0c

Observation e5090340-03b9-4a48-9b23-788f8d82755b · outbound

This paper cites Cehr-bert: Incorporating temporal information from structured ehr data to improve prediction tasks.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Cehr-bert: Incorporating temporal information from structured ehr data to improve prediction tasks

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.699096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.406417Z digest=sha256:f604095c8c78c65a6f17ce36c549633bb3cd86d3cb1f397d680c5f1fb0a55cb5

Observation b0c4495c-dd2a-4c6e-8863-1c6bd951cd3b · outbound

This paper cites CEHR-GPT: Generating Electronic Health Records with Chronological Patient Timelines.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records CEHR-GPT: Generating Electronic Health Records with Chronological Patient Timelines

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T10:43:07.409978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:43:07.409978Z digest=sha256:e730e5baba11b589babafa101d73e3a242cd36e2424f2d79091b3d20adba50b8

Observation ee216f72-493d-4298-b8ba-e98216761651 · outbound

This paper cites Unsupervised pre-training of graph transformers on patient population graphs.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Unsupervised pre-training of graph transformers on patient population graphs

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.687768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.414441Z digest=sha256:e716d05eabfc03f1460d8528a6a89ac6b974ab11387a606d194a2e47a61907a1

Observation faacc7f9-f33d-4ea9-9f46-000e4612df5b · outbound

This paper cites Med-bert: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Med-bert: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.676800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.417998Z digest=sha256:e9093347ea5ed07770de370596dd8485610767938961f79dc40e56b5f6497444

Observation 6ff53d2c-4f6c-4d99-ab56-e3bad6107a36 · outbound

This paper cites Zero shot health trajectory prediction using transformer.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Zero shot health trajectory prediction using transformer

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.665907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.421374Z digest=sha256:95bba9244b53784552a569ee03386ce170f2fbb131c8badba7f7d16b355910b7

Observation 8d993909-8edd-429c-ba8a-8e8a58a12361 · outbound

This paper cites Understanding patient pathways in the context of integrated health care services-implications from a scoping review.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Understanding patient pathways in the context of integrated health care services-implications from a scoping review

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.654681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.424628Z digest=sha256:35f7a137e134e517cccef781a4b6efe0c4a19d848149bcef71b785e52295a9e1

Observation cc2d1a00-6a5c-402d-9c44-b54f23d6e166 · outbound

This paper cites The international classification of diseases: ninth revision (icd-9), 1978.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records The international classification of diseases: ninth revision (icd-9), 1978

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.643319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.427982Z digest=sha256:3fde1d3350d030d55171b731c35ee4cbc7301638648645bf9ac44c76fa13e264

Observation bda0ffb1-fc22-484f-826e-ebc78baf5817 · outbound

This paper cites MOTOR: A Time-To-Event Foundation Model For Structured Medical Records.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records MOTOR: A Time-To-Event Foundation Model For Structured Medical Records

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T10:43:07.431943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:43:07.431943Z digest=sha256:f3ba25f8296b042a815d13a5b7171ed01c1d7b537b10b225ab1e324284478216

Observation ad5c40e5-b720-4d21-82ff-9f0ae2dc02bf · outbound

This paper cites Pereira, and William Bialek.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Pereira, and William Bialek

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.632793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.436258Z digest=sha256:1d2d614bb5799107927ad9f04cea7520a3b6c482922f7f681bc0dd25012f92be

Observation 4d94e5e7-7337-4b82-a2fe-52b3878354c3 · outbound

This paper cites Attention is all you need.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Attention is all you need

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T10:43:07.440017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:43:07.440017Z digest=sha256:eb4aac38231a08d1d0f3cef72e0f189f47d27c4a3068c0e4409656444cc4f68b

Observation 22adc4e7-de31-4706-8853-f2d2b6b9e528 · outbound

This paper cites Mimic-extract: A data extraction, preprocessing, and representation pipeline for mimic-iii.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Mimic-extract: A data extraction, preprocessing, and representation pipeline for mimic-iii

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.616306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.443790Z digest=sha256:2326b71474809ae537e248c1d68bce231c4a34a4faafb60ee0ddbc4d9fab1034

Observation 90e199b4-9d67-4f38-bc98-9974fc6afe81 · outbound

This paper cites Ehrshot: An ehr benchmark for few-shot evaluation of foundation models.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Ehrshot: An ehr benchmark for few-shot evaluation of foundation models

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.605120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.447111Z digest=sha256:812356840b8531ca9940f0618b3b4adad11f1cf7ef3180d0298ae2f89bfc2223

Observation 140c1bc3-3c94-4299-aa26-29a8139d85d0 · outbound

This paper cites Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHRs.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHRs

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T10:43:07.450438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:43:07.450438Z digest=sha256:fe65d97a6203013133d24d4b62763a96056ff4ecd5ab21b177bc654ba5d8b20b

Observation e31e1e98-af17-49c0-89ee-1a7e04b49570 · outbound

This paper cites Qwen2 Technical Report.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Qwen2 Technical Report

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T10:43:07.454178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:43:07.454178Z digest=sha256:c67a3dae977bc81a33683dbaa0174a4b8a75ba0b7c278ed560ea2a03965bf2de

Observation ca301dd1-60d6-4fde-85d9-b2fa83ffe0ae · outbound

This paper cites A large language model for electronic health records.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records A large language model for electronic health records

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:43:07.593288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T10:43:07.458185Z digest=sha256:38b5ff1026f9576e64e273b42a2c548856ff81ec903d16bf748619dd3134ec89

Observation c22be0b3-f03b-4611-82ea-c533712cfaa5 · outbound

This paper cites Transformehr: transformer-based encoder-decoder generative model to enhance prediction of disease outcomes using electronic health records.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records Transformehr: transformer-based encoder-decoder generative model to enhance prediction of disease outcomes using electronic health records

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T10:43:07.461797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:43:07.461797Z digest=sha256:5d050e441652955f94caec449a1ea2f5b25ef77b920d75c56e2f2e4c255d97d8

Observation 2ac36d82-2aea-44a3-b8ed-0370ed4bec60 · outbound

This paper cites EMERGE: Enhancing Multimodal Electronic Health Records Predictive Modeling with Retrieval-Augmented Generation.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records EMERGE: Enhancing Multimodal Electronic Health Records Predictive Modeling with Retrieval-Augmented Generation

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T10:43:07.465363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:43:07.465363Z digest=sha256:0be418fafb452e3c9d273ed554fdb545e194c5b8db93fdfa2c2e63a18daf070a

Observation a1e0f273-70ad-4adc-97ed-bdf2083925e0 · outbound

This paper cites write newline.

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records write newline

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T10:43:07.468962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:43:07.468962Z digest=sha256:4f785bd265f9c51edc14f9f8ec5237c7adb51b9cda1b2fb412da956a7fdee1ab

Pith citing papers

Observation 348a3473-8b1c-4366-8487-6a1e4194eadb · inbound

A Comprehensive Survey of Electronic Health Record Modeling: From Deep Learning Approaches to Large Language Models cites this paper.

A Comprehensive Survey of Electronic Health Record Modeling: From Deep Learning Approaches to Large Language Models EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records

Reference 221

Resolution
unresolved
no resolver link, observed 2026-08-06T16:42:40.840354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:42:40.840354Z digest=sha256:5bf08098942cc1b4a886a3d4dcf8d0287ec14d3069743e34f27ede694b3e5488

Observation 19418c34-731f-4b95-9c78-b9fd3487e69e · inbound

A multimodal and temporal foundation model for virtual patient representations at healthcare system scale cites this paper.

A multimodal and temporal foundation model for virtual patient representations at healthcare system scale EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-08-04T02:23:04.332198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T05:03:40.305624Z digest=sha256:6bc0d5af29312e24d99dcd372c24bc792ad08615d9b21a6ff8ab919d1c536b9d

Observation 84473f2b-14d9-4d7f-8323-f92a32777b27 · inbound

EHR-RAGp: Retrieval-Augmented Prototype-Guided Foundation Model for Electronic Health Records cites this paper.

EHR-RAGp: Retrieval-Augmented Prototype-Guided Foundation Model for Electronic Health Records EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-08-04T02:23:04.332198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-13T03:17:13.143208Z digest=sha256:5323fad08644bc037938deeed155451b75526c225ebc24b432fc01feeeae2ea7

Observation 49c54621-187e-4184-821e-1d14d33774c4 · inbound

Traj-Evolve: A Self-Evolving Multi-Agent System for Patient Trajectory Modeling in Lung Cancer Early Detection cites this paper.

Traj-Evolve: A Self-Evolving Multi-Agent System for Patient Trajectory Modeling in Lung Cancer Early Detection EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records

Reference 29

Resolution
metadata mismatch
arxiv_id, observed 2026-08-04T02:23:04.332198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-28T14:20:06.381334Z digest=sha256:41b71add9497576a4154358877b60b5e6d7ceb97ec7c2284c797e74d5f82d287

Observation 991bc753-6a27-47df-a147-03cf1d676174 · inbound

OphthaDT: Generative Digital Twins for Forecasting Visual Acuity Trajectories in Ophthalmology cites this paper.

OphthaDT: Generative Digital Twins for Forecasting Visual Acuity Trajectories in Ophthalmology EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-08-04T02:23:04.332198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T12:25:49.005706Z digest=sha256:a61160b69321a54cdf575f995678ed4acff21986bba2b871c0ef983c17485e7f