{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:YUFIRJ64GWF7FDDLYZEV4KBCL4","short_pith_number":"pith:YUFIRJ64","canonical_record":{"source":{"id":"1907.06162","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-14T03:50:38Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"fcac3308a8dc2042ff97cc6555d9ac6fc17a8fef645ee03fb88f13dc15dcce12","abstract_canon_sha256":"6cc133298c74b2b99ba4c427e6d3ea38c69f0ba5933f538cad204a54f5f5a1d4"},"schema_version":"1.0"},"canonical_sha256":"c50a88a7dc358bf28c6bc6495e28225f26c42017cf07ba06efd9e1ceb51ff9b8","source":{"kind":"arxiv","id":"1907.06162","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.06162","created_at":"2026-05-17T23:40:38Z"},{"alias_kind":"arxiv_version","alias_value":"1907.06162v1","created_at":"2026-05-17T23:40:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.06162","created_at":"2026-05-17T23:40:38Z"},{"alias_kind":"pith_short_12","alias_value":"YUFIRJ64GWF7","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"YUFIRJ64GWF7FDDL","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"YUFIRJ64","created_at":"2026-05-18T12:33:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:YUFIRJ64GWF7FDDLYZEV4KBCL4","target":"record","payload":{"canonical_record":{"source":{"id":"1907.06162","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-14T03:50:38Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"fcac3308a8dc2042ff97cc6555d9ac6fc17a8fef645ee03fb88f13dc15dcce12","abstract_canon_sha256":"6cc133298c74b2b99ba4c427e6d3ea38c69f0ba5933f538cad204a54f5f5a1d4"},"schema_version":"1.0"},"canonical_sha256":"c50a88a7dc358bf28c6bc6495e28225f26c42017cf07ba06efd9e1ceb51ff9b8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:40:38.345816Z","signature_b64":"tGgObDSklB61rhtnuZ1cV1TdYImAyWGZsWp+l44nyZNB+AMhUDYR17wx43C0AKDNxUO3Dhd5DBVvUq/oqh8IBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c50a88a7dc358bf28c6bc6495e28225f26c42017cf07ba06efd9e1ceb51ff9b8","last_reissued_at":"2026-05-17T23:40:38.345357Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:40:38.345357Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.06162","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":"2026-05-17T23:40:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aqmyDs9KUMBGh0RDeW/PBotMxWXBWpfuxkbBWlZQUHjZqea0a/jF59DhBgTJR4Rzv6kvsBLkFZI6aPUJdDyDDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T06:18:28.833309Z"},"content_sha256":"509cf34c966022cb1d3dbe65c6bd975791c8fa47da85cd5785ef42c840e0a1b9","schema_version":"1.0","event_id":"sha256:509cf34c966022cb1d3dbe65c6bd975791c8fa47da85cd5785ef42c840e0a1b9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:YUFIRJ64GWF7FDDLYZEV4KBCL4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Modeling the Uncertainty in Electronic Health Records: a Bayesian Deep Learning Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Michael Dulin, Mirsad Hadzikadic, Riyi Qiu, Xi Niu, Xin Wang, Yugang Jia","submitted_at":"2019-07-14T03:50:38Z","abstract_excerpt":"Deep learning models have exhibited superior performance in predictive tasks with the explosively increasing Electronic Health Records (EHR). However, due to the lack of transparency, behaviors of deep learning models are difficult to interpret. Without trustworthiness, deep learning models will not be able to assist in the real-world decision-making process of healthcare issues. We propose a deep learning model based on Bayesian Neural Networks (BNN) to predict uncertainty induced by data noise. The uncertainty is introduced to provide model predictions with an extra level of confidence. Our "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.06162","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":"2026-05-17T23:40:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3MmHK26ujxWQBDZWXls4RYb35i7MJRxnn2sy9/rTEAEbvT7f42Doc0AZ0d0gJlgDV4e0CQBlo3U70rWhF42rCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T06:18:28.833908Z"},"content_sha256":"04adc1c5dee1682ee29517ce7bbe63e6628e0e0e9e4011c6a486323fb873c620","schema_version":"1.0","event_id":"sha256:04adc1c5dee1682ee29517ce7bbe63e6628e0e0e9e4011c6a486323fb873c620"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YUFIRJ64GWF7FDDLYZEV4KBCL4/bundle.json","state_url":"https://pith.science/pith/YUFIRJ64GWF7FDDLYZEV4KBCL4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YUFIRJ64GWF7FDDLYZEV4KBCL4/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":"2026-06-07T06:18:28Z","links":{"resolver":"https://pith.science/pith/YUFIRJ64GWF7FDDLYZEV4KBCL4","bundle":"https://pith.science/pith/YUFIRJ64GWF7FDDLYZEV4KBCL4/bundle.json","state":"https://pith.science/pith/YUFIRJ64GWF7FDDLYZEV4KBCL4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YUFIRJ64GWF7FDDLYZEV4KBCL4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:YUFIRJ64GWF7FDDLYZEV4KBCL4","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":"6cc133298c74b2b99ba4c427e6d3ea38c69f0ba5933f538cad204a54f5f5a1d4","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-14T03:50:38Z","title_canon_sha256":"fcac3308a8dc2042ff97cc6555d9ac6fc17a8fef645ee03fb88f13dc15dcce12"},"schema_version":"1.0","source":{"id":"1907.06162","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.06162","created_at":"2026-05-17T23:40:38Z"},{"alias_kind":"arxiv_version","alias_value":"1907.06162v1","created_at":"2026-05-17T23:40:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.06162","created_at":"2026-05-17T23:40:38Z"},{"alias_kind":"pith_short_12","alias_value":"YUFIRJ64GWF7","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"YUFIRJ64GWF7FDDL","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"YUFIRJ64","created_at":"2026-05-18T12:33:33Z"}],"graph_snapshots":[{"event_id":"sha256:04adc1c5dee1682ee29517ce7bbe63e6628e0e0e9e4011c6a486323fb873c620","target":"graph","created_at":"2026-05-17T23:40:38Z","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":"Deep learning models have exhibited superior performance in predictive tasks with the explosively increasing Electronic Health Records (EHR). However, due to the lack of transparency, behaviors of deep learning models are difficult to interpret. Without trustworthiness, deep learning models will not be able to assist in the real-world decision-making process of healthcare issues. We propose a deep learning model based on Bayesian Neural Networks (BNN) to predict uncertainty induced by data noise. The uncertainty is introduced to provide model predictions with an extra level of confidence. Our ","authors_text":"Michael Dulin, Mirsad Hadzikadic, Riyi Qiu, Xi Niu, Xin Wang, Yugang Jia","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-14T03:50:38Z","title":"Modeling the Uncertainty in Electronic Health Records: a Bayesian Deep Learning Approach"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.06162","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":"sha256:509cf34c966022cb1d3dbe65c6bd975791c8fa47da85cd5785ef42c840e0a1b9","target":"record","created_at":"2026-05-17T23:40:38Z","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":"6cc133298c74b2b99ba4c427e6d3ea38c69f0ba5933f538cad204a54f5f5a1d4","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-14T03:50:38Z","title_canon_sha256":"fcac3308a8dc2042ff97cc6555d9ac6fc17a8fef645ee03fb88f13dc15dcce12"},"schema_version":"1.0","source":{"id":"1907.06162","kind":"arxiv","version":1}},"canonical_sha256":"c50a88a7dc358bf28c6bc6495e28225f26c42017cf07ba06efd9e1ceb51ff9b8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c50a88a7dc358bf28c6bc6495e28225f26c42017cf07ba06efd9e1ceb51ff9b8","first_computed_at":"2026-05-17T23:40:38.345357Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:40:38.345357Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tGgObDSklB61rhtnuZ1cV1TdYImAyWGZsWp+l44nyZNB+AMhUDYR17wx43C0AKDNxUO3Dhd5DBVvUq/oqh8IBg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:40:38.345816Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.06162","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:509cf34c966022cb1d3dbe65c6bd975791c8fa47da85cd5785ef42c840e0a1b9","sha256:04adc1c5dee1682ee29517ce7bbe63e6628e0e0e9e4011c6a486323fb873c620"],"state_sha256":"ae97ec05bf9c8d3c8fc9fef93ef74b8c1e41bad124c9c654966c3fcf44f7ad05"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IzG3kiMpgl8hLGErY6pCHiW+TnmHMy2p+whuSiLz3awgWMTGj9auj9RW6fodL986CHOeZWsqrfh90YhXWfuaCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-07T06:18:28.837621Z","bundle_sha256":"f70170865837b772a3c8e1ef498f2056fceb7eda49be9ea4007c8c1dba5ffef4"}}