{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:YOK5X4PS3JGH7M2M7SYFHD6GEK","short_pith_number":"pith:YOK5X4PS","schema_version":"1.0","canonical_sha256":"c395dbf1f2da4c7fb34cfcb0538fc6229e653b21f4b3dbb4402ff6ed4a88e335","source":{"kind":"arxiv","id":"2309.10424","version":1},"attestation_state":"computed","paper":{"title":"Functional requirements to mitigate the Risk of Harm to Patients from Artificial Intelligence in Healthcare","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Ascensi\\'on Do\\~nate-Mart\\'inez, Jaime Cebolla-Cornejo, Jos\\'e Carlos de Bartolom\\'e Cenzano, Juan M. Garc\\'ia-G\\'omez, Vicent Blanes-Selva","submitted_at":"2023-09-19T08:37:22Z","abstract_excerpt":"The Directorate General for Parliamentary Research Services of the European Parliament has prepared a report to the Members of the European Parliament where they enumerate seven main risks of Artificial Intelligence (AI) in medicine and healthcare: patient harm due to AI errors, misuse of medical AI tools, bias in AI and the perpetuation of existing inequities, lack of transparency, privacy and security issues, gaps in accountability, and obstacles in implementation.\n  In this study, we propose fourteen functional requirements that AI systems may implement to reduce the risks associated with t"},"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":"2309.10424","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2023-09-19T08:37:22Z","cross_cats_sorted":[],"title_canon_sha256":"a44b3a8b09306ca21e881ed7e91be9ce5e4a665bfa435ff62a69a059d2926865","abstract_canon_sha256":"32dbd0f2bcd1473d1779db165b54e3a9270ff59bb05ec693d4654a79bd5796c7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:52:11.857419Z","signature_b64":"xDa5N8VZN4U4NkYVaSnC93iCk0rMoiPflJ9ZYcaPz66rQD/VVBOpWwM+Z7MKvzp7a9XqYnHvTbWuFumCYy7vAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c395dbf1f2da4c7fb34cfcb0538fc6229e653b21f4b3dbb4402ff6ed4a88e335","last_reissued_at":"2026-07-05T06:52:11.856861Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:52:11.856861Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Functional requirements to mitigate the Risk of Harm to Patients from Artificial Intelligence in Healthcare","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Ascensi\\'on Do\\~nate-Mart\\'inez, Jaime Cebolla-Cornejo, Jos\\'e Carlos de Bartolom\\'e Cenzano, Juan M. Garc\\'ia-G\\'omez, Vicent Blanes-Selva","submitted_at":"2023-09-19T08:37:22Z","abstract_excerpt":"The Directorate General for Parliamentary Research Services of the European Parliament has prepared a report to the Members of the European Parliament where they enumerate seven main risks of Artificial Intelligence (AI) in medicine and healthcare: patient harm due to AI errors, misuse of medical AI tools, bias in AI and the perpetuation of existing inequities, lack of transparency, privacy and security issues, gaps in accountability, and obstacles in implementation.\n  In this study, we propose fourteen functional requirements that AI systems may implement to reduce the risks associated with t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.10424","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/2309.10424/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":"2309.10424","created_at":"2026-07-05T06:52:11.856932+00:00"},{"alias_kind":"arxiv_version","alias_value":"2309.10424v1","created_at":"2026-07-05T06:52:11.856932+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.10424","created_at":"2026-07-05T06:52:11.856932+00:00"},{"alias_kind":"pith_short_12","alias_value":"YOK5X4PS3JGH","created_at":"2026-07-05T06:52:11.856932+00:00"},{"alias_kind":"pith_short_16","alias_value":"YOK5X4PS3JGH7M2M","created_at":"2026-07-05T06:52:11.856932+00:00"},{"alias_kind":"pith_short_8","alias_value":"YOK5X4PS","created_at":"2026-07-05T06:52:11.856932+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2506.00235","citing_title":"MedOrch: Medical Diagnosis with Tool-Augmented Reasoning Agents for Flexible Extensibility","ref_index":8,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/YOK5X4PS3JGH7M2M7SYFHD6GEK","json":"https://pith.science/pith/YOK5X4PS3JGH7M2M7SYFHD6GEK.json","graph_json":"https://pith.science/api/pith-number/YOK5X4PS3JGH7M2M7SYFHD6GEK/graph.json","events_json":"https://pith.science/api/pith-number/YOK5X4PS3JGH7M2M7SYFHD6GEK/events.json","paper":"https://pith.science/paper/YOK5X4PS"},"agent_actions":{"view_html":"https://pith.science/pith/YOK5X4PS3JGH7M2M7SYFHD6GEK","download_json":"https://pith.science/pith/YOK5X4PS3JGH7M2M7SYFHD6GEK.json","view_paper":"https://pith.science/paper/YOK5X4PS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2309.10424&json=true","fetch_graph":"https://pith.science/api/pith-number/YOK5X4PS3JGH7M2M7SYFHD6GEK/graph.json","fetch_events":"https://pith.science/api/pith-number/YOK5X4PS3JGH7M2M7SYFHD6GEK/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YOK5X4PS3JGH7M2M7SYFHD6GEK/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YOK5X4PS3JGH7M2M7SYFHD6GEK/action/storage_attestation","attest_author":"https://pith.science/pith/YOK5X4PS3JGH7M2M7SYFHD6GEK/action/author_attestation","sign_citation":"https://pith.science/pith/YOK5X4PS3JGH7M2M7SYFHD6GEK/action/citation_signature","submit_replication":"https://pith.science/pith/YOK5X4PS3JGH7M2M7SYFHD6GEK/action/replication_record"}},"created_at":"2026-07-05T06:52:11.856932+00:00","updated_at":"2026-07-05T06:52:11.856932+00:00"}