{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:XT6HOEKR46BRRNICBX24XDHWOR","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":"f980ea3741279ec0838a1f7cd27c76c2d7fedc151286503fcc1eafc6ab6ba354","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-11-26T23:23:29Z","title_canon_sha256":"5df5c77f2e90929540bc5ca69dda58bac49a5217ee648bffd20fc87dbc2db9ee"},"schema_version":"1.0","source":{"id":"1911.13219","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.13219","created_at":"2026-07-05T01:08:25Z"},{"alias_kind":"arxiv_version","alias_value":"1911.13219v3","created_at":"2026-07-05T01:08:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.13219","created_at":"2026-07-05T01:08:25Z"},{"alias_kind":"pith_short_12","alias_value":"XT6HOEKR46BR","created_at":"2026-07-05T01:08:25Z"},{"alias_kind":"pith_short_16","alias_value":"XT6HOEKR46BRRNIC","created_at":"2026-07-05T01:08:25Z"},{"alias_kind":"pith_short_8","alias_value":"XT6HOEKR","created_at":"2026-07-05T01:08:25Z"}],"graph_snapshots":[{"event_id":"sha256:5b68ac1ae6c7e1f0b0ad77af16336ea36d9617cde061e3350a42a0ba9dfb3484","target":"graph","created_at":"2026-07-05T01:08:25Z","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/1911.13219/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose a fully automated algorithm based on a deep learning framework enabling screening of a coronary computed tomography angiography (CCTA) examination for confident detection of the presence or absence of coronary artery atherosclerosis. The system starts with extracting the coronary arteries and their branches from CCTA datasets and representing them with multi-planar reformatted volumes; pre-processing and augmentation techniques are then applied to increase the robustness and generalization ability of the system. A 3-dimensional convolutional neural network (3D-CNN) is utilized to mo","authors_text":"Barbaros S. Erdal, Luciano M. Prevedello, Matthew T. Bigelow, Mutlu Demirer, Richard D. White, Sema Candemir, Vikash Gupta","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-11-26T23:23:29Z","title":"Automated Coronary Artery Atherosclerosis Detection and Weakly Supervised Localization on Coronary CT Angiography with a Deep 3-Dimensional Convolutional Neural Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.13219","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":"sha256:963e2027eb3e1b0e51a75410d56e6fd5fa675391ea5d696c71b51881a02775af","target":"record","created_at":"2026-07-05T01:08:25Z","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":"f980ea3741279ec0838a1f7cd27c76c2d7fedc151286503fcc1eafc6ab6ba354","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-11-26T23:23:29Z","title_canon_sha256":"5df5c77f2e90929540bc5ca69dda58bac49a5217ee648bffd20fc87dbc2db9ee"},"schema_version":"1.0","source":{"id":"1911.13219","kind":"arxiv","version":3}},"canonical_sha256":"bcfc771151e78318b5020df5cb8cf674655d8da4663233c938f3218da8ce8aa2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bcfc771151e78318b5020df5cb8cf674655d8da4663233c938f3218da8ce8aa2","first_computed_at":"2026-07-05T01:08:25.779971Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:08:25.779971Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"80S6YDZMsbBC7gK+0m6VQES0KgwH1oPjT3T5xvynRHKv/wNUvcpqJZhEse1ScDxnSR5SjuTmjmmrBg4FSldXCg==","signature_status":"signed_v1","signed_at":"2026-07-05T01:08:25.780396Z","signed_message":"canonical_sha256_bytes"},"source_id":"1911.13219","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:963e2027eb3e1b0e51a75410d56e6fd5fa675391ea5d696c71b51881a02775af","sha256:5b68ac1ae6c7e1f0b0ad77af16336ea36d9617cde061e3350a42a0ba9dfb3484"],"state_sha256":"66073448c73dce01518cc247c470ad47d435a7d56e337a325feeeb4434373ea7"}