{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:XK3LZS22FPLMKBQNMB2PXP5ERA","short_pith_number":"pith:XK3LZS22","schema_version":"1.0","canonical_sha256":"bab6bccb5a2bd6c5060d6074fbbfa4882bc3a4041ad4f762f5d812cb1cf29bd8","source":{"kind":"arxiv","id":"2310.12677","version":2},"attestation_state":"computed","paper":{"title":"Case-level Breast Cancer Prediction for Real Hospital Settings","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Christin Seifert, Jeroen Geerdink, Jeroen Veltman, J\\\"org Schl\\\"otterer, Maurice van Keulen, Nicola Strisciuglio, Shreyasi Pathak","submitted_at":"2023-10-19T12:14:28Z","abstract_excerpt":"Breast cancer prediction models for mammography assume that annotations are available for individual images or regions of interest (ROIs), and that there is a fixed number of images per patient. These assumptions do not hold in real hospital settings, where clinicians provide only a final diagnosis for the entire mammography exam (case). Since data in real hospital settings scales with continuous patient intake, while manual annotation efforts do not, we develop a framework for case-level breast cancer prediction that does not require any manual annotation and can be trained with case labels r"},"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":"2310.12677","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-10-19T12:14:28Z","cross_cats_sorted":[],"title_canon_sha256":"a2deebc41fb0c14211956f6003a35400c0d841b0adb1ac4d31cf8d5d0af56d37","abstract_canon_sha256":"e6028354e7835250fac141073f3994c7ae289da9ffea2b43366da58a696b6788"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:22:37.437120Z","signature_b64":"UnVRBERDFxAYV51/Ce2pw2+T1HVId/dbew7OgCTviXahTp+0k0Y7EmpsMZfRVQltzHCBMt8k+wHcnT/+rg8nBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bab6bccb5a2bd6c5060d6074fbbfa4882bc3a4041ad4f762f5d812cb1cf29bd8","last_reissued_at":"2026-07-05T09:22:37.436673Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:22:37.436673Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Case-level Breast Cancer Prediction for Real Hospital Settings","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Christin Seifert, Jeroen Geerdink, Jeroen Veltman, J\\\"org Schl\\\"otterer, Maurice van Keulen, Nicola Strisciuglio, Shreyasi Pathak","submitted_at":"2023-10-19T12:14:28Z","abstract_excerpt":"Breast cancer prediction models for mammography assume that annotations are available for individual images or regions of interest (ROIs), and that there is a fixed number of images per patient. These assumptions do not hold in real hospital settings, where clinicians provide only a final diagnosis for the entire mammography exam (case). Since data in real hospital settings scales with continuous patient intake, while manual annotation efforts do not, we develop a framework for case-level breast cancer prediction that does not require any manual annotation and can be trained with case labels r"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.12677","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/2310.12677/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":"2310.12677","created_at":"2026-07-05T09:22:37.436733+00:00"},{"alias_kind":"arxiv_version","alias_value":"2310.12677v2","created_at":"2026-07-05T09:22:37.436733+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.12677","created_at":"2026-07-05T09:22:37.436733+00:00"},{"alias_kind":"pith_short_12","alias_value":"XK3LZS22FPLM","created_at":"2026-07-05T09:22:37.436733+00:00"},{"alias_kind":"pith_short_16","alias_value":"XK3LZS22FPLMKBQN","created_at":"2026-07-05T09:22:37.436733+00:00"},{"alias_kind":"pith_short_8","alias_value":"XK3LZS22","created_at":"2026-07-05T09:22:37.436733+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/XK3LZS22FPLMKBQNMB2PXP5ERA","json":"https://pith.science/pith/XK3LZS22FPLMKBQNMB2PXP5ERA.json","graph_json":"https://pith.science/api/pith-number/XK3LZS22FPLMKBQNMB2PXP5ERA/graph.json","events_json":"https://pith.science/api/pith-number/XK3LZS22FPLMKBQNMB2PXP5ERA/events.json","paper":"https://pith.science/paper/XK3LZS22"},"agent_actions":{"view_html":"https://pith.science/pith/XK3LZS22FPLMKBQNMB2PXP5ERA","download_json":"https://pith.science/pith/XK3LZS22FPLMKBQNMB2PXP5ERA.json","view_paper":"https://pith.science/paper/XK3LZS22","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2310.12677&json=true","fetch_graph":"https://pith.science/api/pith-number/XK3LZS22FPLMKBQNMB2PXP5ERA/graph.json","fetch_events":"https://pith.science/api/pith-number/XK3LZS22FPLMKBQNMB2PXP5ERA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XK3LZS22FPLMKBQNMB2PXP5ERA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XK3LZS22FPLMKBQNMB2PXP5ERA/action/storage_attestation","attest_author":"https://pith.science/pith/XK3LZS22FPLMKBQNMB2PXP5ERA/action/author_attestation","sign_citation":"https://pith.science/pith/XK3LZS22FPLMKBQNMB2PXP5ERA/action/citation_signature","submit_replication":"https://pith.science/pith/XK3LZS22FPLMKBQNMB2PXP5ERA/action/replication_record"}},"created_at":"2026-07-05T09:22:37.436733+00:00","updated_at":"2026-07-05T09:22:37.436733+00:00"}