{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:EAIW7VVEJ63CHAVTFH5FSKCETZ","short_pith_number":"pith:EAIW7VVE","schema_version":"1.0","canonical_sha256":"20116fd6a44fb62382b329fa5928449e7d3511d6a780695876f85664dae69440","source":{"kind":"arxiv","id":"2403.05606","version":1},"attestation_state":"computed","paper":{"title":"A Concept-based Interpretable Model for the Diagnosis of Choroid Neoplasias using Multimodal Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.CV"],"primary_cat":"cs.LG","authors_text":"Dongjun Li, James C. Gee, Lihong Yang, Michael S. Yao, Shi Gu, Wenbin Wei, Wenli Yang, Xuan Yang, Xuehui Shi, Yang Liu, Yifan Wu, Yueming Liu, Yue Yang","submitted_at":"2024-03-08T07:15:53Z","abstract_excerpt":"Diagnosing rare diseases presents a common challenge in clinical practice, necessitating the expertise of specialists for accurate identification. The advent of machine learning offers a promising solution, while the development of such technologies is hindered by the scarcity of data on rare conditions and the demand for models that are both interpretable and trustworthy in a clinical context. Interpretable AI, with its capacity for human-readable outputs, can facilitate validation by clinicians and contribute to medical education. In the current work, we focus on choroid neoplasias, the most"},"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":"2403.05606","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-08T07:15:53Z","cross_cats_sorted":["cs.AI","cs.CL","cs.CV"],"title_canon_sha256":"a97d0aa178cca5604052b1bbf0cccef3f188d8b391c9437b8ea4dd571c042526","abstract_canon_sha256":"a26795acd803ebcce7f8b98147cc57caa40137165bc5d52421b3c007256029b3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:54:10.786438Z","signature_b64":"hPq3OijryHrhD7p5z4ISB+VA0FUFo5X8a2KIFR9xhE8QgWFULWTHWtXTiW+gLGtuPXR1r9+9BHzNCzIk4WwjCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"20116fd6a44fb62382b329fa5928449e7d3511d6a780695876f85664dae69440","last_reissued_at":"2026-07-05T07:54:10.785978Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:54:10.785978Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Concept-based Interpretable Model for the Diagnosis of Choroid Neoplasias using Multimodal Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.CV"],"primary_cat":"cs.LG","authors_text":"Dongjun Li, James C. Gee, Lihong Yang, Michael S. Yao, Shi Gu, Wenbin Wei, Wenli Yang, Xuan Yang, Xuehui Shi, Yang Liu, Yifan Wu, Yueming Liu, Yue Yang","submitted_at":"2024-03-08T07:15:53Z","abstract_excerpt":"Diagnosing rare diseases presents a common challenge in clinical practice, necessitating the expertise of specialists for accurate identification. The advent of machine learning offers a promising solution, while the development of such technologies is hindered by the scarcity of data on rare conditions and the demand for models that are both interpretable and trustworthy in a clinical context. Interpretable AI, with its capacity for human-readable outputs, can facilitate validation by clinicians and contribute to medical education. In the current work, we focus on choroid neoplasias, the most"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.05606","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/2403.05606/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":"2403.05606","created_at":"2026-07-05T07:54:10.786056+00:00"},{"alias_kind":"arxiv_version","alias_value":"2403.05606v1","created_at":"2026-07-05T07:54:10.786056+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.05606","created_at":"2026-07-05T07:54:10.786056+00:00"},{"alias_kind":"pith_short_12","alias_value":"EAIW7VVEJ63C","created_at":"2026-07-05T07:54:10.786056+00:00"},{"alias_kind":"pith_short_16","alias_value":"EAIW7VVEJ63CHAVT","created_at":"2026-07-05T07:54:10.786056+00:00"},{"alias_kind":"pith_short_8","alias_value":"EAIW7VVE","created_at":"2026-07-05T07:54:10.786056+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/EAIW7VVEJ63CHAVTFH5FSKCETZ","json":"https://pith.science/pith/EAIW7VVEJ63CHAVTFH5FSKCETZ.json","graph_json":"https://pith.science/api/pith-number/EAIW7VVEJ63CHAVTFH5FSKCETZ/graph.json","events_json":"https://pith.science/api/pith-number/EAIW7VVEJ63CHAVTFH5FSKCETZ/events.json","paper":"https://pith.science/paper/EAIW7VVE"},"agent_actions":{"view_html":"https://pith.science/pith/EAIW7VVEJ63CHAVTFH5FSKCETZ","download_json":"https://pith.science/pith/EAIW7VVEJ63CHAVTFH5FSKCETZ.json","view_paper":"https://pith.science/paper/EAIW7VVE","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2403.05606&json=true","fetch_graph":"https://pith.science/api/pith-number/EAIW7VVEJ63CHAVTFH5FSKCETZ/graph.json","fetch_events":"https://pith.science/api/pith-number/EAIW7VVEJ63CHAVTFH5FSKCETZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/EAIW7VVEJ63CHAVTFH5FSKCETZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/EAIW7VVEJ63CHAVTFH5FSKCETZ/action/storage_attestation","attest_author":"https://pith.science/pith/EAIW7VVEJ63CHAVTFH5FSKCETZ/action/author_attestation","sign_citation":"https://pith.science/pith/EAIW7VVEJ63CHAVTFH5FSKCETZ/action/citation_signature","submit_replication":"https://pith.science/pith/EAIW7VVEJ63CHAVTFH5FSKCETZ/action/replication_record"}},"created_at":"2026-07-05T07:54:10.786056+00:00","updated_at":"2026-07-05T07:54:10.786056+00:00"}