{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:X7SUUWL3B5MZH5V45267SCPAPU","short_pith_number":"pith:X7SUUWL3","schema_version":"1.0","canonical_sha256":"bfe54a597b0f5993f6bceebdf909e07d3d37a0cbc3b598cfe993d704d20d3a35","source":{"kind":"arxiv","id":"2211.08584","version":3},"attestation_state":"computed","paper":{"title":"Toward expanding the scope of radiology report summarization to multiple anatomies and modalities","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Curtis Langlotz, Jean-Benoit Delbrouck, Maya Varma, Xiang Wan, Zhihong Chen","submitted_at":"2022-11-15T23:57:34Z","abstract_excerpt":"Radiology report summarization (RRS) is a growing area of research. Given the Findings section of a radiology report, the goal is to generate a summary (called an Impression section) that highlights the key observations and conclusions of the radiology study. However, RRS currently faces essential limitations.First, many prior studies conduct experiments on private datasets, preventing reproduction of results and fair comparisons across different systems and solutions. Second, most prior approaches are evaluated solely on chest X-rays. To address these limitations, we propose a dataset (MIMIC-"},"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":"2211.08584","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-11-15T23:57:34Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"fd147d85f857b799db23aaeed0f721f22c355f08692a9d8e07025357a76b7d31","abstract_canon_sha256":"869e6317d95a32530241b0099a2d9b896031c52d2c1895d730f4a60063fe5f83"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:49:54.739436Z","signature_b64":"fRbwLqe3eCof53Jvff4Dps/8o6n933qLiuN8IxWBzaSCAnz3hYZabvxujTKz2As1S7PkaX0Ou1SZzTWFTkb1DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bfe54a597b0f5993f6bceebdf909e07d3d37a0cbc3b598cfe993d704d20d3a35","last_reissued_at":"2026-07-05T07:49:54.738905Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:49:54.738905Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Toward expanding the scope of radiology report summarization to multiple anatomies and modalities","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Curtis Langlotz, Jean-Benoit Delbrouck, Maya Varma, Xiang Wan, Zhihong Chen","submitted_at":"2022-11-15T23:57:34Z","abstract_excerpt":"Radiology report summarization (RRS) is a growing area of research. Given the Findings section of a radiology report, the goal is to generate a summary (called an Impression section) that highlights the key observations and conclusions of the radiology study. However, RRS currently faces essential limitations.First, many prior studies conduct experiments on private datasets, preventing reproduction of results and fair comparisons across different systems and solutions. Second, most prior approaches are evaluated solely on chest X-rays. To address these limitations, we propose a dataset (MIMIC-"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.08584","kind":"arxiv","version":3},"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/2211.08584/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":"2211.08584","created_at":"2026-07-05T07:49:54.738966+00:00"},{"alias_kind":"arxiv_version","alias_value":"2211.08584v3","created_at":"2026-07-05T07:49:54.738966+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.08584","created_at":"2026-07-05T07:49:54.738966+00:00"},{"alias_kind":"pith_short_12","alias_value":"X7SUUWL3B5MZ","created_at":"2026-07-05T07:49:54.738966+00:00"},{"alias_kind":"pith_short_16","alias_value":"X7SUUWL3B5MZH5V4","created_at":"2026-07-05T07:49:54.738966+00:00"},{"alias_kind":"pith_short_8","alias_value":"X7SUUWL3","created_at":"2026-07-05T07:49:54.738966+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2608.03890","citing_title":"CARE-X: Towards Clinically Useful Radiology VLMs with Auxiliary Supervision, Reward-Aligned Learning, and Tool-Augmented Measurement","ref_index":101,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/X7SUUWL3B5MZH5V45267SCPAPU","json":"https://pith.science/pith/X7SUUWL3B5MZH5V45267SCPAPU.json","graph_json":"https://pith.science/api/pith-number/X7SUUWL3B5MZH5V45267SCPAPU/graph.json","events_json":"https://pith.science/api/pith-number/X7SUUWL3B5MZH5V45267SCPAPU/events.json","paper":"https://pith.science/paper/X7SUUWL3"},"agent_actions":{"view_html":"https://pith.science/pith/X7SUUWL3B5MZH5V45267SCPAPU","download_json":"https://pith.science/pith/X7SUUWL3B5MZH5V45267SCPAPU.json","view_paper":"https://pith.science/paper/X7SUUWL3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2211.08584&json=true","fetch_graph":"https://pith.science/api/pith-number/X7SUUWL3B5MZH5V45267SCPAPU/graph.json","fetch_events":"https://pith.science/api/pith-number/X7SUUWL3B5MZH5V45267SCPAPU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/X7SUUWL3B5MZH5V45267SCPAPU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/X7SUUWL3B5MZH5V45267SCPAPU/action/storage_attestation","attest_author":"https://pith.science/pith/X7SUUWL3B5MZH5V45267SCPAPU/action/author_attestation","sign_citation":"https://pith.science/pith/X7SUUWL3B5MZH5V45267SCPAPU/action/citation_signature","submit_replication":"https://pith.science/pith/X7SUUWL3B5MZH5V45267SCPAPU/action/replication_record"}},"created_at":"2026-07-05T07:49:54.738966+00:00","updated_at":"2026-07-05T07:49:54.738966+00:00"}