{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:XXEIIOVVGFAQCGPGAMMU5ZVWFE","short_pith_number":"pith:XXEIIOVV","schema_version":"1.0","canonical_sha256":"bdc8843ab531410119e603194ee6b62938a0919ba3e95b3bba0ed14314deece1","source":{"kind":"arxiv","id":"2501.07166","version":1},"attestation_state":"computed","paper":{"title":"Natural Language-Assisted Multi-modal Medication Recommendation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Helen Meng, Hong Cheng, Jie Tan, Junzhou Huang, Kangfei Zhao, Tian Bian, Tingyang Xu, Yu Rong","submitted_at":"2025-01-13T09:51:50Z","abstract_excerpt":"Combinatorial medication recommendation(CMR) is a fundamental task of healthcare, which offers opportunities for clinical physicians to provide more precise prescriptions for patients with intricate health conditions, particularly in the scenarios of long-term medical care. Previous research efforts have sought to extract meaningful information from electronic health records (EHRs) to facilitate combinatorial medication recommendations. Existing learning-based approaches further consider the chemical structures of medications, but ignore the textual medication descriptions in which the functio"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2501.07166","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-01-13T09:51:50Z","cross_cats_sorted":[],"title_canon_sha256":"6e3bba84342deeeab8bc5f9aed8520a9c4610b519214867c6c8930f5e22904e4","abstract_canon_sha256":"6711925d473535370464492b9f1ed7595facd0b37f1c8fcb9dbaf9a6f41446f0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:00:16.214583Z","signature_b64":"zc8PtoEeX1IU9qLxRfnm+iNP8fjjdMsiY+Tp14vMoaPA9gx9ocM3iDLhNG1KXGwXvCXzrXS+yjZt7lqDpGpXAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bdc8843ab531410119e603194ee6b62938a0919ba3e95b3bba0ed14314deece1","last_reissued_at":"2026-07-05T10:00:16.214090Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:00:16.214090Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Natural Language-Assisted Multi-modal Medication Recommendation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Helen Meng, Hong Cheng, Jie Tan, Junzhou Huang, Kangfei Zhao, Tian Bian, Tingyang Xu, Yu Rong","submitted_at":"2025-01-13T09:51:50Z","abstract_excerpt":"Combinatorial medication recommendation(CMR) is a fundamental task of healthcare, which offers opportunities for clinical physicians to provide more precise prescriptions for patients with intricate health conditions, particularly in the scenarios of long-term medical care. Previous research efforts have sought to extract meaningful information from electronic health records (EHRs) to facilitate combinatorial medication recommendations. Existing learning-based approaches further consider the chemical structures of medications, but ignore the textual medication descriptions in which the functio"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.07166","kind":"arxiv","version":1},"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/2501.07166/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2501.07166","created_at":"2026-07-05T10:00:16.214204+00:00"},{"alias_kind":"arxiv_version","alias_value":"2501.07166v1","created_at":"2026-07-05T10:00:16.214204+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.07166","created_at":"2026-07-05T10:00:16.214204+00:00"},{"alias_kind":"pith_short_12","alias_value":"XXEIIOVVGFAQ","created_at":"2026-07-05T10:00:16.214204+00:00"},{"alias_kind":"pith_short_16","alias_value":"XXEIIOVVGFAQCGPG","created_at":"2026-07-05T10:00:16.214204+00:00"},{"alias_kind":"pith_short_8","alias_value":"XXEIIOVV","created_at":"2026-07-05T10:00:16.214204+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/XXEIIOVVGFAQCGPGAMMU5ZVWFE","json":"https://pith.science/pith/XXEIIOVVGFAQCGPGAMMU5ZVWFE.json","graph_json":"https://pith.science/api/pith-number/XXEIIOVVGFAQCGPGAMMU5ZVWFE/graph.json","events_json":"https://pith.science/api/pith-number/XXEIIOVVGFAQCGPGAMMU5ZVWFE/events.json","paper":"https://pith.science/paper/XXEIIOVV"},"agent_actions":{"view_html":"https://pith.science/pith/XXEIIOVVGFAQCGPGAMMU5ZVWFE","download_json":"https://pith.science/pith/XXEIIOVVGFAQCGPGAMMU5ZVWFE.json","view_paper":"https://pith.science/paper/XXEIIOVV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2501.07166&json=true","fetch_graph":"https://pith.science/api/pith-number/XXEIIOVVGFAQCGPGAMMU5ZVWFE/graph.json","fetch_events":"https://pith.science/api/pith-number/XXEIIOVVGFAQCGPGAMMU5ZVWFE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XXEIIOVVGFAQCGPGAMMU5ZVWFE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XXEIIOVVGFAQCGPGAMMU5ZVWFE/action/storage_attestation","attest_author":"https://pith.science/pith/XXEIIOVVGFAQCGPGAMMU5ZVWFE/action/author_attestation","sign_citation":"https://pith.science/pith/XXEIIOVVGFAQCGPGAMMU5ZVWFE/action/citation_signature","submit_replication":"https://pith.science/pith/XXEIIOVVGFAQCGPGAMMU5ZVWFE/action/replication_record"}},"created_at":"2026-07-05T10:00:16.214204+00:00","updated_at":"2026-07-05T10:00:16.214204+00:00"}