{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:RAVMWCCQLGCL42QQHUWRTV7ICH","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"b15094af2b15e98d1f6ee535da93a5249656d116005502ebaf3d00cd4135cb56","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-01T11:14:45Z","title_canon_sha256":"cc6a23626ea71d3de65eb089743296277c094c50c30ab0420ebcc78e4ecd68a0"},"schema_version":"1.0","source":{"id":"2507.02987","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.02987","created_at":"2026-07-05T11:42:31Z"},{"alias_kind":"arxiv_version","alias_value":"2507.02987v3","created_at":"2026-07-05T11:42:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.02987","created_at":"2026-07-05T11:42:31Z"},{"alias_kind":"pith_short_12","alias_value":"RAVMWCCQLGCL","created_at":"2026-07-05T11:42:31Z"},{"alias_kind":"pith_short_16","alias_value":"RAVMWCCQLGCL42QQ","created_at":"2026-07-05T11:42:31Z"},{"alias_kind":"pith_short_8","alias_value":"RAVMWCCQ","created_at":"2026-07-05T11:42:31Z"}],"graph_snapshots":[{"event_id":"sha256:1fa81041ebba0cf3029b24ceff4e1b064104444b44cb6c26e90509d9b8c6cc34","target":"graph","created_at":"2026-07-05T11:42:31Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2507.02987/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Building generalizable medical AI systems requires pretraining strategies that are data-efficient and domain-aware. Unlike internet-scale corpora, clinical datasets such as MIMIC-CXR offer limited image counts and scarce annotations, but exhibit rich internal structure through multi-view imaging. We propose a self-supervised framework that leverages the inherent structure of medical datasets. Specifically, we treat paired chest X-rays (i.e., frontal and lateral views) as natural positive pairs, learning to reconstruct each view from sparse patches while aligning their latent embeddings. Our me","authors_text":"Alain Ryser, Andrea Agostini, Farhad Nooralahzadeh, Julia E. Vogt, Michael Krauthammer, Moritz Vandenhirtz, Nicolas Deperrois, Samuel Ruiperez-Campillo, Sonia Laguna, Thomas M. Sutter","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-01T11:14:45Z","title":"Leveraging the Structure of Medical Data for Improved Representation Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.02987","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:13539bdc66992ac071c0e58485422c51dd807459f29fb786a93cba2d5a397820","target":"record","created_at":"2026-07-05T11:42:31Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"b15094af2b15e98d1f6ee535da93a5249656d116005502ebaf3d00cd4135cb56","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-01T11:14:45Z","title_canon_sha256":"cc6a23626ea71d3de65eb089743296277c094c50c30ab0420ebcc78e4ecd68a0"},"schema_version":"1.0","source":{"id":"2507.02987","kind":"arxiv","version":3}},"canonical_sha256":"882acb08505984be6a103d2d19d7e811c056e26ebb10687b26bda0620a705dbc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"882acb08505984be6a103d2d19d7e811c056e26ebb10687b26bda0620a705dbc","first_computed_at":"2026-07-05T11:42:31.821386Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:42:31.821386Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"u5xinp0GvyMuVQOYJvz+sawCTq7CfSwiOFS7t46S81ueJ58ABq4jR5L3oHDBsvo6xMhcKEXwwyFDN+anHE+KCg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:42:31.821929Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.02987","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:13539bdc66992ac071c0e58485422c51dd807459f29fb786a93cba2d5a397820","sha256:1fa81041ebba0cf3029b24ceff4e1b064104444b44cb6c26e90509d9b8c6cc34"],"state_sha256":"7a5a50e929a5509d426df987229653b070bff8ec776365caeb2244cc0184e0a9"}