{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:24KWFZRWD2UNHVARKUL6MOHSRY","short_pith_number":"pith:24KWFZRW","canonical_record":{"source":{"id":"2402.01077","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-02T00:31:01Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"0aaed4253c46064651745968fb1c980a4d7a40f1baa0a5e09ed6816197a35867","abstract_canon_sha256":"6df0456659c9ee4b949123b5e5edc2f77d11a70b1c0109e9c6e369ae06470c19"},"schema_version":"1.0"},"canonical_sha256":"d71562e6361ea8d3d4115517e638f28e31ba9a789da839e44b9a77cc32db0b55","source":{"kind":"arxiv","id":"2402.01077","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.01077","created_at":"2026-07-05T08:54:46Z"},{"alias_kind":"arxiv_version","alias_value":"2402.01077v2","created_at":"2026-07-05T08:54:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.01077","created_at":"2026-07-05T08:54:46Z"},{"alias_kind":"pith_short_12","alias_value":"24KWFZRWD2UN","created_at":"2026-07-05T08:54:46Z"},{"alias_kind":"pith_short_16","alias_value":"24KWFZRWD2UNHVAR","created_at":"2026-07-05T08:54:46Z"},{"alias_kind":"pith_short_8","alias_value":"24KWFZRW","created_at":"2026-07-05T08:54:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:24KWFZRWD2UNHVARKUL6MOHSRY","target":"record","payload":{"canonical_record":{"source":{"id":"2402.01077","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-02T00:31:01Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"0aaed4253c46064651745968fb1c980a4d7a40f1baa0a5e09ed6816197a35867","abstract_canon_sha256":"6df0456659c9ee4b949123b5e5edc2f77d11a70b1c0109e9c6e369ae06470c19"},"schema_version":"1.0"},"canonical_sha256":"d71562e6361ea8d3d4115517e638f28e31ba9a789da839e44b9a77cc32db0b55","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:54:46.883934Z","signature_b64":"7UA0mA5S2ZfFI80DSLw78Dl4g8J3RhnKGLf30VtlBGYILPNelK/4PkYtHwuk/Ekoi/WXnwqizOPRuO3yczt6DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d71562e6361ea8d3d4115517e638f28e31ba9a789da839e44b9a77cc32db0b55","last_reissued_at":"2026-07-05T08:54:46.883480Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:54:46.883480Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.01077","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:54:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wqLA3gTChWgLod7kRU0Q3JSDxSQ+iZL9x9Lsz4DidV2Tp7gQNUk+voQkAfSIYXgesSag5rvEvGwe2Ny5JcVrAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T23:53:35.142790Z"},"content_sha256":"7b6317da0af065049824a31396d9fa65330ca3348cf449ab2bf1741ff61c4a4c","schema_version":"1.0","event_id":"sha256:7b6317da0af065049824a31396d9fa65330ca3348cf449ab2bf1741ff61c4a4c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:24KWFZRWD2UNHVARKUL6MOHSRY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Recent Advances in Predictive Modeling with Electronic Health Records","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Aofei Chang, Cao Xiao, Fenglong Ma, Guanjie Huang, Jiaqi Wang, Jimeng Sun, Junyu Luo, Muchao Ye, Xiaochen Wang, Yuan Zhong, Ziyi Yin","submitted_at":"2024-02-02T00:31:01Z","abstract_excerpt":"The development of electronic health records (EHR) systems has enabled the collection of a vast amount of digitized patient data. However, utilizing EHR data for predictive modeling presents several challenges due to its unique characteristics. With the advancements in machine learning techniques, deep learning has demonstrated its superiority in various applications, including healthcare. This survey systematically reviews recent advances in deep learning-based predictive models using EHR data. Specifically, we begin by introducing the background of EHR data and providing a mathematical defin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.01077","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2402.01077/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:54:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TpI2+39X7v8k+wHRQhXNOiKAWtHi+Wu/rZpZkN0ZunoOwqNBt2BHg9bjXdeDryP1h/wqPqDZBYTBx3+C0roNBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T23:53:35.143403Z"},"content_sha256":"2e0562f7b657cb6aa2a49b538255c8888157439bc8a149951b4f264e6d7927da","schema_version":"1.0","event_id":"sha256:2e0562f7b657cb6aa2a49b538255c8888157439bc8a149951b4f264e6d7927da"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/24KWFZRWD2UNHVARKUL6MOHSRY/bundle.json","state_url":"https://pith.science/pith/24KWFZRWD2UNHVARKUL6MOHSRY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/24KWFZRWD2UNHVARKUL6MOHSRY/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-07T23:53:35Z","links":{"resolver":"https://pith.science/pith/24KWFZRWD2UNHVARKUL6MOHSRY","bundle":"https://pith.science/pith/24KWFZRWD2UNHVARKUL6MOHSRY/bundle.json","state":"https://pith.science/pith/24KWFZRWD2UNHVARKUL6MOHSRY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/24KWFZRWD2UNHVARKUL6MOHSRY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:24KWFZRWD2UNHVARKUL6MOHSRY","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"6df0456659c9ee4b949123b5e5edc2f77d11a70b1c0109e9c6e369ae06470c19","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-02T00:31:01Z","title_canon_sha256":"0aaed4253c46064651745968fb1c980a4d7a40f1baa0a5e09ed6816197a35867"},"schema_version":"1.0","source":{"id":"2402.01077","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.01077","created_at":"2026-07-05T08:54:46Z"},{"alias_kind":"arxiv_version","alias_value":"2402.01077v2","created_at":"2026-07-05T08:54:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.01077","created_at":"2026-07-05T08:54:46Z"},{"alias_kind":"pith_short_12","alias_value":"24KWFZRWD2UN","created_at":"2026-07-05T08:54:46Z"},{"alias_kind":"pith_short_16","alias_value":"24KWFZRWD2UNHVAR","created_at":"2026-07-05T08:54:46Z"},{"alias_kind":"pith_short_8","alias_value":"24KWFZRW","created_at":"2026-07-05T08:54:46Z"}],"graph_snapshots":[{"event_id":"sha256:2e0562f7b657cb6aa2a49b538255c8888157439bc8a149951b4f264e6d7927da","target":"graph","created_at":"2026-07-05T08:54:46Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2402.01077/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The development of electronic health records (EHR) systems has enabled the collection of a vast amount of digitized patient data. However, utilizing EHR data for predictive modeling presents several challenges due to its unique characteristics. With the advancements in machine learning techniques, deep learning has demonstrated its superiority in various applications, including healthcare. This survey systematically reviews recent advances in deep learning-based predictive models using EHR data. Specifically, we begin by introducing the background of EHR data and providing a mathematical defin","authors_text":"Aofei Chang, Cao Xiao, Fenglong Ma, Guanjie Huang, Jiaqi Wang, Jimeng Sun, Junyu Luo, Muchao Ye, Xiaochen Wang, Yuan Zhong, Ziyi Yin","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-02T00:31:01Z","title":"Recent Advances in Predictive Modeling with Electronic Health Records"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.01077","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:7b6317da0af065049824a31396d9fa65330ca3348cf449ab2bf1741ff61c4a4c","target":"record","created_at":"2026-07-05T08:54:46Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"6df0456659c9ee4b949123b5e5edc2f77d11a70b1c0109e9c6e369ae06470c19","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-02T00:31:01Z","title_canon_sha256":"0aaed4253c46064651745968fb1c980a4d7a40f1baa0a5e09ed6816197a35867"},"schema_version":"1.0","source":{"id":"2402.01077","kind":"arxiv","version":2}},"canonical_sha256":"d71562e6361ea8d3d4115517e638f28e31ba9a789da839e44b9a77cc32db0b55","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d71562e6361ea8d3d4115517e638f28e31ba9a789da839e44b9a77cc32db0b55","first_computed_at":"2026-07-05T08:54:46.883480Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:54:46.883480Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7UA0mA5S2ZfFI80DSLw78Dl4g8J3RhnKGLf30VtlBGYILPNelK/4PkYtHwuk/Ekoi/WXnwqizOPRuO3yczt6DQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:54:46.883934Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.01077","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7b6317da0af065049824a31396d9fa65330ca3348cf449ab2bf1741ff61c4a4c","sha256:2e0562f7b657cb6aa2a49b538255c8888157439bc8a149951b4f264e6d7927da"],"state_sha256":"56cf853f0975d1d59b0ae2edc84c459a74b79397ece2490f7950bcdbcd922dfa"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HhwC+bkwcoa2reqGmql/tBp+25v9PUrnYkmEZecfevIc+munE6iLmQSO7hAtEmJn8NfX/l1SX/YvDX0Iq0UXCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T23:53:35.147513Z","bundle_sha256":"d23ad73520f780d8891e5f0e283e8b63122de80a9fd7de0a8559b94ad1fb4c12"}}