{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:GKS5NNKVEXAMNVCUU66NBCYQUY","short_pith_number":"pith:GKS5NNKV","schema_version":"1.0","canonical_sha256":"32a5d6b55525c0c6d454a7bcd08b10a602f61b5186a91d08f045039b3e528a2a","source":{"kind":"arxiv","id":"2308.05110","version":1},"attestation_state":"computed","paper":{"title":"Can Attention Be Used to Explain EHR-Based Mortality Prediction Tasks: A Case Study on Hemorrhagic Stroke","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Forhan Bin Emdad, Jiayi Yuan, Karim Hanna, Qizhang Feng, Xia Hu, Zhe He","submitted_at":"2023-08-04T04:28:07Z","abstract_excerpt":"Stroke is a significant cause of mortality and morbidity, necessitating early predictive strategies to minimize risks. Traditional methods for evaluating patients, such as Acute Physiology and Chronic Health Evaluation (APACHE II, IV) and Simplified Acute Physiology Score III (SAPS III), have limited accuracy and interpretability. This paper proposes a novel approach: an interpretable, attention-based transformer model for early stroke mortality prediction. This model seeks to address the limitations of previous predictive models, providing both interpretability (providing clear, understandabl"},"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":"2308.05110","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-08-04T04:28:07Z","cross_cats_sorted":[],"title_canon_sha256":"163f956af7dac249c6b527be496c772781365fe5653ee7ed3d39906962a53585","abstract_canon_sha256":"2fddb29bb3d38d8cf615a1dfbe755bed9cde66a01a8f06a3b87f7c5e0e9ff92b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:39:55.673889Z","signature_b64":"8EHZ0OG/IAXbq2zwF0Qi2QxzfyUkGly80twcUENp0CNb/4CzltbNmFi7ukY7JptZU7NSv1dYRJ9uWwZhWUIkAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"32a5d6b55525c0c6d454a7bcd08b10a602f61b5186a91d08f045039b3e528a2a","last_reissued_at":"2026-07-05T06:39:55.673481Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:39:55.673481Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Can Attention Be Used to Explain EHR-Based Mortality Prediction Tasks: A Case Study on Hemorrhagic Stroke","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Forhan Bin Emdad, Jiayi Yuan, Karim Hanna, Qizhang Feng, Xia Hu, Zhe He","submitted_at":"2023-08-04T04:28:07Z","abstract_excerpt":"Stroke is a significant cause of mortality and morbidity, necessitating early predictive strategies to minimize risks. Traditional methods for evaluating patients, such as Acute Physiology and Chronic Health Evaluation (APACHE II, IV) and Simplified Acute Physiology Score III (SAPS III), have limited accuracy and interpretability. This paper proposes a novel approach: an interpretable, attention-based transformer model for early stroke mortality prediction. This model seeks to address the limitations of previous predictive models, providing both interpretability (providing clear, understandabl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.05110","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/2308.05110/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":"2308.05110","created_at":"2026-07-05T06:39:55.673537+00:00"},{"alias_kind":"arxiv_version","alias_value":"2308.05110v1","created_at":"2026-07-05T06:39:55.673537+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.05110","created_at":"2026-07-05T06:39:55.673537+00:00"},{"alias_kind":"pith_short_12","alias_value":"GKS5NNKVEXAM","created_at":"2026-07-05T06:39:55.673537+00:00"},{"alias_kind":"pith_short_16","alias_value":"GKS5NNKVEXAMNVCU","created_at":"2026-07-05T06:39:55.673537+00:00"},{"alias_kind":"pith_short_8","alias_value":"GKS5NNKV","created_at":"2026-07-05T06:39:55.673537+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/GKS5NNKVEXAMNVCUU66NBCYQUY","json":"https://pith.science/pith/GKS5NNKVEXAMNVCUU66NBCYQUY.json","graph_json":"https://pith.science/api/pith-number/GKS5NNKVEXAMNVCUU66NBCYQUY/graph.json","events_json":"https://pith.science/api/pith-number/GKS5NNKVEXAMNVCUU66NBCYQUY/events.json","paper":"https://pith.science/paper/GKS5NNKV"},"agent_actions":{"view_html":"https://pith.science/pith/GKS5NNKVEXAMNVCUU66NBCYQUY","download_json":"https://pith.science/pith/GKS5NNKVEXAMNVCUU66NBCYQUY.json","view_paper":"https://pith.science/paper/GKS5NNKV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2308.05110&json=true","fetch_graph":"https://pith.science/api/pith-number/GKS5NNKVEXAMNVCUU66NBCYQUY/graph.json","fetch_events":"https://pith.science/api/pith-number/GKS5NNKVEXAMNVCUU66NBCYQUY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/GKS5NNKVEXAMNVCUU66NBCYQUY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/GKS5NNKVEXAMNVCUU66NBCYQUY/action/storage_attestation","attest_author":"https://pith.science/pith/GKS5NNKVEXAMNVCUU66NBCYQUY/action/author_attestation","sign_citation":"https://pith.science/pith/GKS5NNKVEXAMNVCUU66NBCYQUY/action/citation_signature","submit_replication":"https://pith.science/pith/GKS5NNKVEXAMNVCUU66NBCYQUY/action/replication_record"}},"created_at":"2026-07-05T06:39:55.673537+00:00","updated_at":"2026-07-05T06:39:55.673537+00:00"}