{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:HZ4KJOFZZFSUBOYN5RKRSUXNB2","short_pith_number":"pith:HZ4KJOFZ","schema_version":"1.0","canonical_sha256":"3e78a4b8b9c96540bb0dec551952ed0e98738334cd9c8b29e7b6dbdb76b6fa36","source":{"kind":"arxiv","id":"2204.10716","version":2},"attestation_state":"computed","paper":{"title":"Hierarchical Label-wise Attention Transformer Model for Explainable ICD Coding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.LG","authors_text":"Anthony Nguyen, Leibo Liu, Louisa Jorm, Oscar Perez-Concha, Vicki Bennett","submitted_at":"2022-04-22T14:12:22Z","abstract_excerpt":"International Classification of Diseases (ICD) coding plays an important role in systematically classifying morbidity and mortality data. In this study, we propose a hierarchical label-wise attention Transformer model (HiLAT) for the explainable prediction of ICD codes from clinical documents. HiLAT firstly fine-tunes a pretrained Transformer model to represent the tokens of clinical documents. We subsequently employ a two-level hierarchical label-wise attention mechanism that creates label-specific document representations. These representations are in turn used by a feed-forward neural netwo"},"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":"2204.10716","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-04-22T14:12:22Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"9e75f9484ba0252a96719253a1ed8036d3fec64ab3b80f4f5e3a012c5e0297b5","abstract_canon_sha256":"08764108ef651cff891b9312bfdb4d3d6b9735bffb06e901a99a3caa208b238b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:02:41.999488Z","signature_b64":"hgMxY8ZKFxROHGtyD+uqW++RS1+PX4q3MCJgMeWpjxq0/T/DKzxnj2QJI0sjD/5bXrpHLwc1m1mDjCkEJvcoCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3e78a4b8b9c96540bb0dec551952ed0e98738334cd9c8b29e7b6dbdb76b6fa36","last_reissued_at":"2026-07-05T05:02:41.999013Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:02:41.999013Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Hierarchical Label-wise Attention Transformer Model for Explainable ICD Coding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.LG","authors_text":"Anthony Nguyen, Leibo Liu, Louisa Jorm, Oscar Perez-Concha, Vicki Bennett","submitted_at":"2022-04-22T14:12:22Z","abstract_excerpt":"International Classification of Diseases (ICD) coding plays an important role in systematically classifying morbidity and mortality data. In this study, we propose a hierarchical label-wise attention Transformer model (HiLAT) for the explainable prediction of ICD codes from clinical documents. HiLAT firstly fine-tunes a pretrained Transformer model to represent the tokens of clinical documents. We subsequently employ a two-level hierarchical label-wise attention mechanism that creates label-specific document representations. These representations are in turn used by a feed-forward neural netwo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2204.10716","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/2204.10716/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":"2204.10716","created_at":"2026-07-05T05:02:41.999087+00:00"},{"alias_kind":"arxiv_version","alias_value":"2204.10716v2","created_at":"2026-07-05T05:02:41.999087+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2204.10716","created_at":"2026-07-05T05:02:41.999087+00:00"},{"alias_kind":"pith_short_12","alias_value":"HZ4KJOFZZFSU","created_at":"2026-07-05T05:02:41.999087+00:00"},{"alias_kind":"pith_short_16","alias_value":"HZ4KJOFZZFSUBOYN","created_at":"2026-07-05T05:02:41.999087+00:00"},{"alias_kind":"pith_short_8","alias_value":"HZ4KJOFZ","created_at":"2026-07-05T05:02:41.999087+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/HZ4KJOFZZFSUBOYN5RKRSUXNB2","json":"https://pith.science/pith/HZ4KJOFZZFSUBOYN5RKRSUXNB2.json","graph_json":"https://pith.science/api/pith-number/HZ4KJOFZZFSUBOYN5RKRSUXNB2/graph.json","events_json":"https://pith.science/api/pith-number/HZ4KJOFZZFSUBOYN5RKRSUXNB2/events.json","paper":"https://pith.science/paper/HZ4KJOFZ"},"agent_actions":{"view_html":"https://pith.science/pith/HZ4KJOFZZFSUBOYN5RKRSUXNB2","download_json":"https://pith.science/pith/HZ4KJOFZZFSUBOYN5RKRSUXNB2.json","view_paper":"https://pith.science/paper/HZ4KJOFZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2204.10716&json=true","fetch_graph":"https://pith.science/api/pith-number/HZ4KJOFZZFSUBOYN5RKRSUXNB2/graph.json","fetch_events":"https://pith.science/api/pith-number/HZ4KJOFZZFSUBOYN5RKRSUXNB2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HZ4KJOFZZFSUBOYN5RKRSUXNB2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HZ4KJOFZZFSUBOYN5RKRSUXNB2/action/storage_attestation","attest_author":"https://pith.science/pith/HZ4KJOFZZFSUBOYN5RKRSUXNB2/action/author_attestation","sign_citation":"https://pith.science/pith/HZ4KJOFZZFSUBOYN5RKRSUXNB2/action/citation_signature","submit_replication":"https://pith.science/pith/HZ4KJOFZZFSUBOYN5RKRSUXNB2/action/replication_record"}},"created_at":"2026-07-05T05:02:41.999087+00:00","updated_at":"2026-07-05T05:02:41.999087+00:00"}