{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:BRJPN2RQII77YH62XMOSNK22LQ","short_pith_number":"pith:BRJPN2RQ","canonical_record":{"source":{"id":"1711.11097","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-29T20:41:05Z","cross_cats_sorted":[],"title_canon_sha256":"f88c2653ea7f7f668679c710e450a4741a00d239bfe0559a62fb66e2e6d2144c","abstract_canon_sha256":"118ccde93826c6dd1abfed9926ec9c39bb16ba5706a0d228b1f079581f401d94"},"schema_version":"1.0"},"canonical_sha256":"0c52f6ea30423ffc1fdabb1d26ab5a5c0c4c37eec04899175cdd817b28f30c40","source":{"kind":"arxiv","id":"1711.11097","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.11097","created_at":"2026-05-18T00:29:12Z"},{"alias_kind":"arxiv_version","alias_value":"1711.11097v1","created_at":"2026-05-18T00:29:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.11097","created_at":"2026-05-18T00:29:12Z"},{"alias_kind":"pith_short_12","alias_value":"BRJPN2RQII77","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_16","alias_value":"BRJPN2RQII77YH62","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_8","alias_value":"BRJPN2RQ","created_at":"2026-05-18T12:31:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:BRJPN2RQII77YH62XMOSNK22LQ","target":"record","payload":{"canonical_record":{"source":{"id":"1711.11097","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-29T20:41:05Z","cross_cats_sorted":[],"title_canon_sha256":"f88c2653ea7f7f668679c710e450a4741a00d239bfe0559a62fb66e2e6d2144c","abstract_canon_sha256":"118ccde93826c6dd1abfed9926ec9c39bb16ba5706a0d228b1f079581f401d94"},"schema_version":"1.0"},"canonical_sha256":"0c52f6ea30423ffc1fdabb1d26ab5a5c0c4c37eec04899175cdd817b28f30c40","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:29:12.502373Z","signature_b64":"eAihU6vnv3JjYaAhs4rnvtbtfQZhJxJa9iABfbIM7LjjKgNYFmB15/3JI0mgHBQxZxVNyNyvqv/VGMBRHeZzBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0c52f6ea30423ffc1fdabb1d26ab5a5c0c4c37eec04899175cdd817b28f30c40","last_reissued_at":"2026-05-18T00:29:12.501763Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:29:12.501763Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1711.11097","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:29:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EBGdG6XwzQDxx6Fz4Rr7t5FMCj/38SavsVWVfyAy4ay3CbCWxjuLKRAsWNNFWSFArDUVJPvvFXVePvtkNtg4CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T08:52:40.505772Z"},"content_sha256":"f6bb98f655082a7d79a357abb5142fb5537d635a8b68260757f21eab845331b6","schema_version":"1.0","event_id":"sha256:f6bb98f655082a7d79a357abb5142fb5537d635a8b68260757f21eab845331b6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:BRJPN2RQII77YH62XMOSNK22LQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Learning for identifying radiogenomic associations in breast cancer","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ashirbani Saha, Ehab AlBadawy, Jun Zhang, Maciej A. Mazurowski, Michael R. Harowicz, Zhe Zhu","submitted_at":"2017-11-29T20:41:05Z","abstract_excerpt":"Purpose: To determine whether deep learning models can distinguish between breast cancer molecular subtypes based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Materials and methods: In this institutional review board-approved single-center study, we analyzed DCE-MR images of 270 patients at our institution. Lesions of interest were identified by radiologists. The task was to automatically determine whether the tumor is of the Luminal A subtype or of another subtype based on the MR image patches representing the tumor. Three different deep learning approaches were used to "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.11097","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":""},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:29:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kbIvem9av6L2PtpEYlhLEipr5CfIrrH3z0o1CJU+5KKPyqFDmV4NhYqP6ZlOg5InfdKxG0Ns6JWyYkQ/EzfbDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T08:52:40.506327Z"},"content_sha256":"1e6bb9e74e8cf53c3824e175a16d352faca88110aa9e078ce24486ba4ee00cff","schema_version":"1.0","event_id":"sha256:1e6bb9e74e8cf53c3824e175a16d352faca88110aa9e078ce24486ba4ee00cff"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BRJPN2RQII77YH62XMOSNK22LQ/bundle.json","state_url":"https://pith.science/pith/BRJPN2RQII77YH62XMOSNK22LQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BRJPN2RQII77YH62XMOSNK22LQ/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-30T08:52:40Z","links":{"resolver":"https://pith.science/pith/BRJPN2RQII77YH62XMOSNK22LQ","bundle":"https://pith.science/pith/BRJPN2RQII77YH62XMOSNK22LQ/bundle.json","state":"https://pith.science/pith/BRJPN2RQII77YH62XMOSNK22LQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BRJPN2RQII77YH62XMOSNK22LQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:BRJPN2RQII77YH62XMOSNK22LQ","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":"118ccde93826c6dd1abfed9926ec9c39bb16ba5706a0d228b1f079581f401d94","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-29T20:41:05Z","title_canon_sha256":"f88c2653ea7f7f668679c710e450a4741a00d239bfe0559a62fb66e2e6d2144c"},"schema_version":"1.0","source":{"id":"1711.11097","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.11097","created_at":"2026-05-18T00:29:12Z"},{"alias_kind":"arxiv_version","alias_value":"1711.11097v1","created_at":"2026-05-18T00:29:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.11097","created_at":"2026-05-18T00:29:12Z"},{"alias_kind":"pith_short_12","alias_value":"BRJPN2RQII77","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_16","alias_value":"BRJPN2RQII77YH62","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_8","alias_value":"BRJPN2RQ","created_at":"2026-05-18T12:31:08Z"}],"graph_snapshots":[{"event_id":"sha256:1e6bb9e74e8cf53c3824e175a16d352faca88110aa9e078ce24486ba4ee00cff","target":"graph","created_at":"2026-05-18T00:29:12Z","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"},"paper":{"abstract_excerpt":"Purpose: To determine whether deep learning models can distinguish between breast cancer molecular subtypes based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Materials and methods: In this institutional review board-approved single-center study, we analyzed DCE-MR images of 270 patients at our institution. Lesions of interest were identified by radiologists. The task was to automatically determine whether the tumor is of the Luminal A subtype or of another subtype based on the MR image patches representing the tumor. Three different deep learning approaches were used to ","authors_text":"Ashirbani Saha, Ehab AlBadawy, Jun Zhang, Maciej A. Mazurowski, Michael R. Harowicz, Zhe Zhu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-29T20:41:05Z","title":"Deep Learning for identifying radiogenomic associations in breast cancer"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.11097","kind":"arxiv","version":1},"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:f6bb98f655082a7d79a357abb5142fb5537d635a8b68260757f21eab845331b6","target":"record","created_at":"2026-05-18T00:29:12Z","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":"118ccde93826c6dd1abfed9926ec9c39bb16ba5706a0d228b1f079581f401d94","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-29T20:41:05Z","title_canon_sha256":"f88c2653ea7f7f668679c710e450a4741a00d239bfe0559a62fb66e2e6d2144c"},"schema_version":"1.0","source":{"id":"1711.11097","kind":"arxiv","version":1}},"canonical_sha256":"0c52f6ea30423ffc1fdabb1d26ab5a5c0c4c37eec04899175cdd817b28f30c40","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0c52f6ea30423ffc1fdabb1d26ab5a5c0c4c37eec04899175cdd817b28f30c40","first_computed_at":"2026-05-18T00:29:12.501763Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:29:12.501763Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"eAihU6vnv3JjYaAhs4rnvtbtfQZhJxJa9iABfbIM7LjjKgNYFmB15/3JI0mgHBQxZxVNyNyvqv/VGMBRHeZzBg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:29:12.502373Z","signed_message":"canonical_sha256_bytes"},"source_id":"1711.11097","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f6bb98f655082a7d79a357abb5142fb5537d635a8b68260757f21eab845331b6","sha256:1e6bb9e74e8cf53c3824e175a16d352faca88110aa9e078ce24486ba4ee00cff"],"state_sha256":"4ff852a15af3889721b8db802aaf494c7e4aad107f05a56d58574bac5f768577"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hvL4qhwenA4m+1B1OsB3TpONBYemu18neBUGSB6utcTNRnMwaJdYFLTNcK6AMk7E2LJLiUOLZiike1PfC6cTCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T08:52:40.508806Z","bundle_sha256":"ea6aac3ad5d24a90441fa90c538d0ca1bc14eff5ed82cf60d3fd7ae5b064e36e"}}