{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:J56EYT5ZWA65UXRX2HZ2RKWLIK","short_pith_number":"pith:J56EYT5Z","schema_version":"1.0","canonical_sha256":"4f7c4c4fb9b03dda5e37d1f3a8aacb429fe384fd06d2f245f134e67f86a3b88b","source":{"kind":"arxiv","id":"1608.00704","version":3},"attestation_state":"computed","paper":{"title":"Identifiable Phenotyping using Constrained Non-Negative Matrix Factorization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"David Sontag, Joydeep Ghosh, Shalmali Joshi, Suriya Gunasekar","submitted_at":"2016-08-02T06:03:53Z","abstract_excerpt":"This work proposes a new algorithm for automated and simultaneous phenotyping of multiple co-occurring medical conditions, also referred as comorbidities, using clinical notes from the electronic health records (EHRs). A basic latent factor estimation technique of non-negative matrix factorization (NMF) is augmented with domain specific constraints to obtain sparse latent factors that are anchored to a fixed set of chronic conditions. The proposed anchoring mechanism ensures a one-to-one identifiable and interpretable mapping between the latent factors and the target comorbidities. Qualitative"},"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":"1608.00704","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-08-02T06:03:53Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"ee24b115909e89c0a2e3113e92e7d395ada5571d445311cfc432b9310d4cc9ab","abstract_canon_sha256":"a02f5964cdb8b58cddeda7bc6870b0ad1700c39d16880bec395ed37ae3598f32"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:04:17.966788Z","signature_b64":"jLFWnJfF22dLxq/T7hhsJB4coV6wBiezhUtHS1tDoSxVwCP/yEPXh/ZcFFRAbPwCXdTnlcvjWA7jb0/NleOfAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4f7c4c4fb9b03dda5e37d1f3a8aacb429fe384fd06d2f245f134e67f86a3b88b","last_reissued_at":"2026-05-18T01:04:17.966346Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:04:17.966346Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Identifiable Phenotyping using Constrained Non-Negative Matrix Factorization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"David Sontag, Joydeep Ghosh, Shalmali Joshi, Suriya Gunasekar","submitted_at":"2016-08-02T06:03:53Z","abstract_excerpt":"This work proposes a new algorithm for automated and simultaneous phenotyping of multiple co-occurring medical conditions, also referred as comorbidities, using clinical notes from the electronic health records (EHRs). A basic latent factor estimation technique of non-negative matrix factorization (NMF) is augmented with domain specific constraints to obtain sparse latent factors that are anchored to a fixed set of chronic conditions. The proposed anchoring mechanism ensures a one-to-one identifiable and interpretable mapping between the latent factors and the target comorbidities. Qualitative"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1608.00704","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"1608.00704","created_at":"2026-05-18T01:04:17.966409+00:00"},{"alias_kind":"arxiv_version","alias_value":"1608.00704v3","created_at":"2026-05-18T01:04:17.966409+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1608.00704","created_at":"2026-05-18T01:04:17.966409+00:00"},{"alias_kind":"pith_short_12","alias_value":"J56EYT5ZWA65","created_at":"2026-05-18T12:30:22.444734+00:00"},{"alias_kind":"pith_short_16","alias_value":"J56EYT5ZWA65UXRX","created_at":"2026-05-18T12:30:22.444734+00:00"},{"alias_kind":"pith_short_8","alias_value":"J56EYT5Z","created_at":"2026-05-18T12:30:22.444734+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/J56EYT5ZWA65UXRX2HZ2RKWLIK","json":"https://pith.science/pith/J56EYT5ZWA65UXRX2HZ2RKWLIK.json","graph_json":"https://pith.science/api/pith-number/J56EYT5ZWA65UXRX2HZ2RKWLIK/graph.json","events_json":"https://pith.science/api/pith-number/J56EYT5ZWA65UXRX2HZ2RKWLIK/events.json","paper":"https://pith.science/paper/J56EYT5Z"},"agent_actions":{"view_html":"https://pith.science/pith/J56EYT5ZWA65UXRX2HZ2RKWLIK","download_json":"https://pith.science/pith/J56EYT5ZWA65UXRX2HZ2RKWLIK.json","view_paper":"https://pith.science/paper/J56EYT5Z","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1608.00704&json=true","fetch_graph":"https://pith.science/api/pith-number/J56EYT5ZWA65UXRX2HZ2RKWLIK/graph.json","fetch_events":"https://pith.science/api/pith-number/J56EYT5ZWA65UXRX2HZ2RKWLIK/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/J56EYT5ZWA65UXRX2HZ2RKWLIK/action/timestamp_anchor","attest_storage":"https://pith.science/pith/J56EYT5ZWA65UXRX2HZ2RKWLIK/action/storage_attestation","attest_author":"https://pith.science/pith/J56EYT5ZWA65UXRX2HZ2RKWLIK/action/author_attestation","sign_citation":"https://pith.science/pith/J56EYT5ZWA65UXRX2HZ2RKWLIK/action/citation_signature","submit_replication":"https://pith.science/pith/J56EYT5ZWA65UXRX2HZ2RKWLIK/action/replication_record"}},"created_at":"2026-05-18T01:04:17.966409+00:00","updated_at":"2026-05-18T01:04:17.966409+00:00"}