{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:4SSQMTIZHEFGZCRNDYKPD2TWEP","short_pith_number":"pith:4SSQMTIZ","canonical_record":{"source":{"id":"1807.06144","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-07-16T22:53:46Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"66055822c3e5dc9bd49b105316dacbdbc53a55960336a7864ae082ff6574dad9","abstract_canon_sha256":"e7debc2bd8ed9c1a78fbf288809bdde6606453bf1a9eeb05f175f352abd148fa"},"schema_version":"1.0"},"canonical_sha256":"e4a5064d19390a6c8a2d1e14f1ea7623d9edca1863a219c9a7843abc41973326","source":{"kind":"arxiv","id":"1807.06144","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1807.06144","created_at":"2026-05-18T00:03:41Z"},{"alias_kind":"arxiv_version","alias_value":"1807.06144v1","created_at":"2026-05-18T00:03:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.06144","created_at":"2026-05-18T00:03:41Z"},{"alias_kind":"pith_short_12","alias_value":"4SSQMTIZHEFG","created_at":"2026-05-18T12:32:05Z"},{"alias_kind":"pith_short_16","alias_value":"4SSQMTIZHEFGZCRN","created_at":"2026-05-18T12:32:05Z"},{"alias_kind":"pith_short_8","alias_value":"4SSQMTIZ","created_at":"2026-05-18T12:32:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:4SSQMTIZHEFGZCRNDYKPD2TWEP","target":"record","payload":{"canonical_record":{"source":{"id":"1807.06144","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-07-16T22:53:46Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"66055822c3e5dc9bd49b105316dacbdbc53a55960336a7864ae082ff6574dad9","abstract_canon_sha256":"e7debc2bd8ed9c1a78fbf288809bdde6606453bf1a9eeb05f175f352abd148fa"},"schema_version":"1.0"},"canonical_sha256":"e4a5064d19390a6c8a2d1e14f1ea7623d9edca1863a219c9a7843abc41973326","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:03:41.123834Z","signature_b64":"YytHVFFD2yOocbWZCXnh+C5C9L0trjEjSsWLaoWVCTAIInlMNdjxso/KH/s6yoWtsRCMfUet87MJc1RGGwhFBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e4a5064d19390a6c8a2d1e14f1ea7623d9edca1863a219c9a7843abc41973326","last_reissued_at":"2026-05-18T00:03:41.123395Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:03:41.123395Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1807.06144","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":"2026-05-18T00:03:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"V9tFffcU9d64GBTAcNRo3QWDxUIGzWNEkqFNmtKIz5pVG8LKaT+ClcoKJa/5B2yjhkpfIvxqxvNvHGGFgQ3SDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T06:34:58.128186Z"},"content_sha256":"156cbfbc76b2424cdcd0455c60d7ac9feb72257553c30b38d5c1509badd7533a","schema_version":"1.0","event_id":"sha256:156cbfbc76b2424cdcd0455c60d7ac9feb72257553c30b38d5c1509badd7533a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:4SSQMTIZHEFGZCRNDYKPD2TWEP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Longitudinal detection of radiological abnormalities with time-modulated LSTM","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.LG"],"primary_cat":"stat.ML","authors_text":"Giovanni Montana, Ruggiero Santeramo, Samuel Withey","submitted_at":"2018-07-16T22:53:46Z","abstract_excerpt":"Convolutional neural networks (CNNs) have been successfully employed in recent years for the detection of radiological abnormalities in medical images such as plain x-rays. To date, most studies use CNNs on individual examinations in isolation and discard previously available clinical information. In this study we set out to explore whether Long-Short-Term-Memory networks (LSTMs) can be used to improve classification performance when modelling the entire sequence of radiographs that may be available for a given patient, including their reports. A limitation of traditional LSTMs, though, is tha"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.06144","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":"2026-05-18T00:03:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nBKnMxJ5yBiOgxgodD7KxXWe4GQ+vVzsAzCzUZvNXtbOFw4vNOroRQCUMc0JFS7BEPdJApIzpEoVKebqVXBwCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T06:34:58.128561Z"},"content_sha256":"7a9e2b509265c0992924ad3816eca8365cb76b7d47686e6c2dd5a2b8b751588b","schema_version":"1.0","event_id":"sha256:7a9e2b509265c0992924ad3816eca8365cb76b7d47686e6c2dd5a2b8b751588b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4SSQMTIZHEFGZCRNDYKPD2TWEP/bundle.json","state_url":"https://pith.science/pith/4SSQMTIZHEFGZCRNDYKPD2TWEP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4SSQMTIZHEFGZCRNDYKPD2TWEP/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":"2026-06-03T06:34:58Z","links":{"resolver":"https://pith.science/pith/4SSQMTIZHEFGZCRNDYKPD2TWEP","bundle":"https://pith.science/pith/4SSQMTIZHEFGZCRNDYKPD2TWEP/bundle.json","state":"https://pith.science/pith/4SSQMTIZHEFGZCRNDYKPD2TWEP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4SSQMTIZHEFGZCRNDYKPD2TWEP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:4SSQMTIZHEFGZCRNDYKPD2TWEP","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":"e7debc2bd8ed9c1a78fbf288809bdde6606453bf1a9eeb05f175f352abd148fa","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-07-16T22:53:46Z","title_canon_sha256":"66055822c3e5dc9bd49b105316dacbdbc53a55960336a7864ae082ff6574dad9"},"schema_version":"1.0","source":{"id":"1807.06144","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1807.06144","created_at":"2026-05-18T00:03:41Z"},{"alias_kind":"arxiv_version","alias_value":"1807.06144v1","created_at":"2026-05-18T00:03:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.06144","created_at":"2026-05-18T00:03:41Z"},{"alias_kind":"pith_short_12","alias_value":"4SSQMTIZHEFG","created_at":"2026-05-18T12:32:05Z"},{"alias_kind":"pith_short_16","alias_value":"4SSQMTIZHEFGZCRN","created_at":"2026-05-18T12:32:05Z"},{"alias_kind":"pith_short_8","alias_value":"4SSQMTIZ","created_at":"2026-05-18T12:32:05Z"}],"graph_snapshots":[{"event_id":"sha256:7a9e2b509265c0992924ad3816eca8365cb76b7d47686e6c2dd5a2b8b751588b","target":"graph","created_at":"2026-05-18T00:03:41Z","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":"Convolutional neural networks (CNNs) have been successfully employed in recent years for the detection of radiological abnormalities in medical images such as plain x-rays. To date, most studies use CNNs on individual examinations in isolation and discard previously available clinical information. In this study we set out to explore whether Long-Short-Term-Memory networks (LSTMs) can be used to improve classification performance when modelling the entire sequence of radiographs that may be available for a given patient, including their reports. A limitation of traditional LSTMs, though, is tha","authors_text":"Giovanni Montana, Ruggiero Santeramo, Samuel Withey","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-07-16T22:53:46Z","title":"Longitudinal detection of radiological abnormalities with time-modulated LSTM"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.06144","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":"sha256:156cbfbc76b2424cdcd0455c60d7ac9feb72257553c30b38d5c1509badd7533a","target":"record","created_at":"2026-05-18T00:03:41Z","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":"e7debc2bd8ed9c1a78fbf288809bdde6606453bf1a9eeb05f175f352abd148fa","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-07-16T22:53:46Z","title_canon_sha256":"66055822c3e5dc9bd49b105316dacbdbc53a55960336a7864ae082ff6574dad9"},"schema_version":"1.0","source":{"id":"1807.06144","kind":"arxiv","version":1}},"canonical_sha256":"e4a5064d19390a6c8a2d1e14f1ea7623d9edca1863a219c9a7843abc41973326","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e4a5064d19390a6c8a2d1e14f1ea7623d9edca1863a219c9a7843abc41973326","first_computed_at":"2026-05-18T00:03:41.123395Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:03:41.123395Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YytHVFFD2yOocbWZCXnh+C5C9L0trjEjSsWLaoWVCTAIInlMNdjxso/KH/s6yoWtsRCMfUet87MJc1RGGwhFBQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:03:41.123834Z","signed_message":"canonical_sha256_bytes"},"source_id":"1807.06144","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:156cbfbc76b2424cdcd0455c60d7ac9feb72257553c30b38d5c1509badd7533a","sha256:7a9e2b509265c0992924ad3816eca8365cb76b7d47686e6c2dd5a2b8b751588b"],"state_sha256":"01c7d4ada427d2587d3131d1105e4e2d5c472fe4040a449bb57467323ef4d5f3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"50RRtXKlEHYVV5z/cQqEsVAzkM5HmjX4nUjucXW6zywAyzMTd44Zp4+z6uol0WfhUUCEHg2XUrB+lS9uBcDACQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T06:34:58.130648Z","bundle_sha256":"6b0ec2c01e56fa95cb3008d7d4087d0305abbb6f481c5d08c08bb4ea87ec3317"}}