{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:KTWEL4R7TW7VTHG7NTLE5V3UNV","short_pith_number":"pith:KTWEL4R7","canonical_record":{"source":{"id":"1810.08503","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-19T13:48:58Z","cross_cats_sorted":[],"title_canon_sha256":"4b61bd2c916c248135b360f21f85f74963ce4cbe1f24853b324352d8879773ce","abstract_canon_sha256":"0f450923403dceadf0fe72a9ab7a143e023c6e0bca5341ed4359c5073394dc2e"},"schema_version":"1.0"},"canonical_sha256":"54ec45f23f9dbf599cdf6cd64ed7746d770989134e8f1c0678bf339ebf22386d","source":{"kind":"arxiv","id":"1810.08503","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.08503","created_at":"2026-05-18T00:02:47Z"},{"alias_kind":"arxiv_version","alias_value":"1810.08503v1","created_at":"2026-05-18T00:02:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.08503","created_at":"2026-05-18T00:02:47Z"},{"alias_kind":"pith_short_12","alias_value":"KTWEL4R7TW7V","created_at":"2026-05-18T12:32:33Z"},{"alias_kind":"pith_short_16","alias_value":"KTWEL4R7TW7VTHG7","created_at":"2026-05-18T12:32:33Z"},{"alias_kind":"pith_short_8","alias_value":"KTWEL4R7","created_at":"2026-05-18T12:32:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:KTWEL4R7TW7VTHG7NTLE5V3UNV","target":"record","payload":{"canonical_record":{"source":{"id":"1810.08503","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-19T13:48:58Z","cross_cats_sorted":[],"title_canon_sha256":"4b61bd2c916c248135b360f21f85f74963ce4cbe1f24853b324352d8879773ce","abstract_canon_sha256":"0f450923403dceadf0fe72a9ab7a143e023c6e0bca5341ed4359c5073394dc2e"},"schema_version":"1.0"},"canonical_sha256":"54ec45f23f9dbf599cdf6cd64ed7746d770989134e8f1c0678bf339ebf22386d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:02:47.932741Z","signature_b64":"G/Cs/ScZw+Dyh3pB+0ISQLPqp6BN4zhtHumOfcdRviKW3EO+vth7/qLmpqvk6SmdTYrmzBS6juknOm/KWq/8DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"54ec45f23f9dbf599cdf6cd64ed7746d770989134e8f1c0678bf339ebf22386d","last_reissued_at":"2026-05-18T00:02:47.932308Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:02:47.932308Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1810.08503","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":"2026-05-18T00:02:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NJvPGMTgNBpsJAzG9/FispQrXJSr10JHllAjasnxWtNssOrKwLqX6huHDzI3kDbUMmWnyMJGNNyB17YC+B6FCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T04:47:30.891797Z"},"content_sha256":"d443edb2431e0018e13ae861c53a13ef7a7fd6d08cab7e3802b4bea702516310","schema_version":"1.0","event_id":"sha256:d443edb2431e0018e13ae861c53a13ef7a7fd6d08cab7e3802b4bea702516310"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:KTWEL4R7TW7VTHG7NTLE5V3UNV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Hybrid deep neural networks for all-cause Mortality Prediction from LDCT Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ge Wang, Hengtao Guo, Mannudeep K. Kalra, Pingkun Yan, Ruben De Man","submitted_at":"2018-10-19T13:48:58Z","abstract_excerpt":"Known for its high morbidity and mortality rates, lung cancer poses a significant threat to human health and well-being. However, the same population is also at high risk for other deadly diseases, such as cardiovascular disease. Since Low-Dose CT (LDCT) has been shown to significantly improve the lung cancer diagnosis accuracy, it will be very useful for clinical practice to predict the all-cause mortality for lung cancer patients to take corresponding actions. In this paper, we propose a deep learning based method, which takes both chest LDCT image patches and coronary artery calcification r"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.08503","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":"2026-05-18T00:02:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"J4C0MLvJAKSGHf21dYosk4fSwDDN8Prh7/pkXX3n71kH/WDBgnourYKE9vAfmnfWZ+9WW8Vlv/T7lNG1RLw4CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T04:47:30.892441Z"},"content_sha256":"8fe30299a6ee0d5f31f605acf236a0d36a0ac413de5d21b4c612b354387db4d6","schema_version":"1.0","event_id":"sha256:8fe30299a6ee0d5f31f605acf236a0d36a0ac413de5d21b4c612b354387db4d6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KTWEL4R7TW7VTHG7NTLE5V3UNV/bundle.json","state_url":"https://pith.science/pith/KTWEL4R7TW7VTHG7NTLE5V3UNV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KTWEL4R7TW7VTHG7NTLE5V3UNV/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":"2026-05-27T04:47:30Z","links":{"resolver":"https://pith.science/pith/KTWEL4R7TW7VTHG7NTLE5V3UNV","bundle":"https://pith.science/pith/KTWEL4R7TW7VTHG7NTLE5V3UNV/bundle.json","state":"https://pith.science/pith/KTWEL4R7TW7VTHG7NTLE5V3UNV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KTWEL4R7TW7VTHG7NTLE5V3UNV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:KTWEL4R7TW7VTHG7NTLE5V3UNV","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":"0f450923403dceadf0fe72a9ab7a143e023c6e0bca5341ed4359c5073394dc2e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-19T13:48:58Z","title_canon_sha256":"4b61bd2c916c248135b360f21f85f74963ce4cbe1f24853b324352d8879773ce"},"schema_version":"1.0","source":{"id":"1810.08503","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.08503","created_at":"2026-05-18T00:02:47Z"},{"alias_kind":"arxiv_version","alias_value":"1810.08503v1","created_at":"2026-05-18T00:02:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.08503","created_at":"2026-05-18T00:02:47Z"},{"alias_kind":"pith_short_12","alias_value":"KTWEL4R7TW7V","created_at":"2026-05-18T12:32:33Z"},{"alias_kind":"pith_short_16","alias_value":"KTWEL4R7TW7VTHG7","created_at":"2026-05-18T12:32:33Z"},{"alias_kind":"pith_short_8","alias_value":"KTWEL4R7","created_at":"2026-05-18T12:32:33Z"}],"graph_snapshots":[{"event_id":"sha256:8fe30299a6ee0d5f31f605acf236a0d36a0ac413de5d21b4c612b354387db4d6","target":"graph","created_at":"2026-05-18T00:02:47Z","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":"Known for its high morbidity and mortality rates, lung cancer poses a significant threat to human health and well-being. However, the same population is also at high risk for other deadly diseases, such as cardiovascular disease. Since Low-Dose CT (LDCT) has been shown to significantly improve the lung cancer diagnosis accuracy, it will be very useful for clinical practice to predict the all-cause mortality for lung cancer patients to take corresponding actions. In this paper, we propose a deep learning based method, which takes both chest LDCT image patches and coronary artery calcification r","authors_text":"Ge Wang, Hengtao Guo, Mannudeep K. Kalra, Pingkun Yan, Ruben De Man","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-19T13:48:58Z","title":"Hybrid deep neural networks for all-cause Mortality Prediction from LDCT Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.08503","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:d443edb2431e0018e13ae861c53a13ef7a7fd6d08cab7e3802b4bea702516310","target":"record","created_at":"2026-05-18T00:02:47Z","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":"0f450923403dceadf0fe72a9ab7a143e023c6e0bca5341ed4359c5073394dc2e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-19T13:48:58Z","title_canon_sha256":"4b61bd2c916c248135b360f21f85f74963ce4cbe1f24853b324352d8879773ce"},"schema_version":"1.0","source":{"id":"1810.08503","kind":"arxiv","version":1}},"canonical_sha256":"54ec45f23f9dbf599cdf6cd64ed7746d770989134e8f1c0678bf339ebf22386d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"54ec45f23f9dbf599cdf6cd64ed7746d770989134e8f1c0678bf339ebf22386d","first_computed_at":"2026-05-18T00:02:47.932308Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:02:47.932308Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"G/Cs/ScZw+Dyh3pB+0ISQLPqp6BN4zhtHumOfcdRviKW3EO+vth7/qLmpqvk6SmdTYrmzBS6juknOm/KWq/8DA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:02:47.932741Z","signed_message":"canonical_sha256_bytes"},"source_id":"1810.08503","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d443edb2431e0018e13ae861c53a13ef7a7fd6d08cab7e3802b4bea702516310","sha256:8fe30299a6ee0d5f31f605acf236a0d36a0ac413de5d21b4c612b354387db4d6"],"state_sha256":"8a51ac3ea2f321cae97771689f225234b96398bbe6d1477e52fed96e6d3dedab"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ReYWhYyoZmLLIo5hBOivHrexk75rYPc+79dhnnH0nZ0OnY6k595un/IQ/aXJGQwB/zNt7e4TSBKzbNA5QneqCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T04:47:30.895938Z","bundle_sha256":"7b4589078f5abd8f509c0602b3dd128ac18bc63848992b5f638788bcf472eb53"}}