{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:HYRIG7V4GLWSNLTADYWU3CDYL6","short_pith_number":"pith:HYRIG7V4","canonical_record":{"source":{"id":"1802.03689","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-11T03:50:41Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"493103a66cce057a1a3da9f416971b24fe1f7c679a4f9097dd0fa28f7c27a6ca","abstract_canon_sha256":"6d0a3efbabe2c45f71c81c855d24361a1223860318a8fa0c5680847a711d5455"},"schema_version":"1.0"},"canonical_sha256":"3e22837ebc32ed26ae601e2d4d88785fbe0790353f832166928dc129d02a71bd","source":{"kind":"arxiv","id":"1802.03689","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.03689","created_at":"2026-05-18T00:23:50Z"},{"alias_kind":"arxiv_version","alias_value":"1802.03689v1","created_at":"2026-05-18T00:23:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.03689","created_at":"2026-05-18T00:23:50Z"},{"alias_kind":"pith_short_12","alias_value":"HYRIG7V4GLWS","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"HYRIG7V4GLWSNLTA","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"HYRIG7V4","created_at":"2026-05-18T12:32:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:HYRIG7V4GLWSNLTADYWU3CDYL6","target":"record","payload":{"canonical_record":{"source":{"id":"1802.03689","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-11T03:50:41Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"493103a66cce057a1a3da9f416971b24fe1f7c679a4f9097dd0fa28f7c27a6ca","abstract_canon_sha256":"6d0a3efbabe2c45f71c81c855d24361a1223860318a8fa0c5680847a711d5455"},"schema_version":"1.0"},"canonical_sha256":"3e22837ebc32ed26ae601e2d4d88785fbe0790353f832166928dc129d02a71bd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:23:50.759128Z","signature_b64":"NMJBawlmc0/Nu9XXLYOE/4raiyE0Gz9UUerczEzS6MDdccWWBbbE8V0jZ+QLiS2gROjj1ipVVfDNzLGJ1bHEBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3e22837ebc32ed26ae601e2d4d88785fbe0790353f832166928dc129d02a71bd","last_reissued_at":"2026-05-18T00:23:50.758201Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:23:50.758201Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1802.03689","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":"2026-05-18T00:23:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"m3YE766A+G4qhWdGvUqhA31y+wnneR+ZlixzU0s1prz9aGDCWhVnGeneCES/zsbg5cw+qSJbdwaCkMnifX2+Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-20T03:23:42.432445Z"},"content_sha256":"7cc7ad8dc85985d9f51c1434bfd24570917f9f1f17556b3cda042b648ebcdcbf","schema_version":"1.0","event_id":"sha256:7cc7ad8dc85985d9f51c1434bfd24570917f9f1f17556b3cda042b648ebcdcbf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:HYRIG7V4GLWSNLTADYWU3CDYL6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Dual Control Memory Augmented Neural Networks for Treatment Recommendations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Hung Le, Svetha Venkatesh, Truyen Tran","submitted_at":"2018-02-11T03:50:41Z","abstract_excerpt":"Machine-assisted treatment recommendations hold a promise to reduce physician time and decision errors. We formulate the task as a sequence-to-sequence prediction model that takes the entire time-ordered medical history as input, and predicts a sequence of future clinical procedures and medications. It is built on the premise that an effective treatment plan may have long-term dependencies from previous medical history. We approach the problem by using a memory-augmented neural network, in particular, by leveraging the recent differentiable neural computer that consists of a neural controller "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.03689","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":"2026-05-18T00:23:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"O8LECHtAp0ad5xoNoWFxthz8qUpwJyUY0Ve8pWs1ujD5dlHXZPRPKgDJGug+7YGJFk7bnPFRPbkGD5bT1gfwAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-20T03:23:42.433269Z"},"content_sha256":"482c39205ce709204cc30d054c81f4a751c0e29aba3761085ac72e589749fd73","schema_version":"1.0","event_id":"sha256:482c39205ce709204cc30d054c81f4a751c0e29aba3761085ac72e589749fd73"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HYRIG7V4GLWSNLTADYWU3CDYL6/bundle.json","state_url":"https://pith.science/pith/HYRIG7V4GLWSNLTADYWU3CDYL6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HYRIG7V4GLWSNLTADYWU3CDYL6/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":"2026-05-20T03:23:42Z","links":{"resolver":"https://pith.science/pith/HYRIG7V4GLWSNLTADYWU3CDYL6","bundle":"https://pith.science/pith/HYRIG7V4GLWSNLTADYWU3CDYL6/bundle.json","state":"https://pith.science/pith/HYRIG7V4GLWSNLTADYWU3CDYL6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HYRIG7V4GLWSNLTADYWU3CDYL6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:HYRIG7V4GLWSNLTADYWU3CDYL6","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":"6d0a3efbabe2c45f71c81c855d24361a1223860318a8fa0c5680847a711d5455","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-11T03:50:41Z","title_canon_sha256":"493103a66cce057a1a3da9f416971b24fe1f7c679a4f9097dd0fa28f7c27a6ca"},"schema_version":"1.0","source":{"id":"1802.03689","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.03689","created_at":"2026-05-18T00:23:50Z"},{"alias_kind":"arxiv_version","alias_value":"1802.03689v1","created_at":"2026-05-18T00:23:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.03689","created_at":"2026-05-18T00:23:50Z"},{"alias_kind":"pith_short_12","alias_value":"HYRIG7V4GLWS","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"HYRIG7V4GLWSNLTA","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"HYRIG7V4","created_at":"2026-05-18T12:32:28Z"}],"graph_snapshots":[{"event_id":"sha256:482c39205ce709204cc30d054c81f4a751c0e29aba3761085ac72e589749fd73","target":"graph","created_at":"2026-05-18T00:23:50Z","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":"Machine-assisted treatment recommendations hold a promise to reduce physician time and decision errors. We formulate the task as a sequence-to-sequence prediction model that takes the entire time-ordered medical history as input, and predicts a sequence of future clinical procedures and medications. It is built on the premise that an effective treatment plan may have long-term dependencies from previous medical history. We approach the problem by using a memory-augmented neural network, in particular, by leveraging the recent differentiable neural computer that consists of a neural controller ","authors_text":"Hung Le, Svetha Venkatesh, Truyen Tran","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-11T03:50:41Z","title":"Dual Control Memory Augmented Neural Networks for Treatment Recommendations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.03689","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":"sha256:7cc7ad8dc85985d9f51c1434bfd24570917f9f1f17556b3cda042b648ebcdcbf","target":"record","created_at":"2026-05-18T00:23:50Z","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":"6d0a3efbabe2c45f71c81c855d24361a1223860318a8fa0c5680847a711d5455","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-11T03:50:41Z","title_canon_sha256":"493103a66cce057a1a3da9f416971b24fe1f7c679a4f9097dd0fa28f7c27a6ca"},"schema_version":"1.0","source":{"id":"1802.03689","kind":"arxiv","version":1}},"canonical_sha256":"3e22837ebc32ed26ae601e2d4d88785fbe0790353f832166928dc129d02a71bd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3e22837ebc32ed26ae601e2d4d88785fbe0790353f832166928dc129d02a71bd","first_computed_at":"2026-05-18T00:23:50.758201Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:23:50.758201Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NMJBawlmc0/Nu9XXLYOE/4raiyE0Gz9UUerczEzS6MDdccWWBbbE8V0jZ+QLiS2gROjj1ipVVfDNzLGJ1bHEBw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:23:50.759128Z","signed_message":"canonical_sha256_bytes"},"source_id":"1802.03689","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7cc7ad8dc85985d9f51c1434bfd24570917f9f1f17556b3cda042b648ebcdcbf","sha256:482c39205ce709204cc30d054c81f4a751c0e29aba3761085ac72e589749fd73"],"state_sha256":"5379f7b225daaa779b7f1d19f2f5a6367c1f5eb245da70440072433be24dd74e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E59aqamFkaMHnXU1uPKQKiirE+ORLnrNB4Edp1i3Jc3YHtPgNhOuciqqFOw+ZCclNQdqWh0k2Sn1FsLTN2kIAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-20T03:23:42.438639Z","bundle_sha256":"227c2c67f3edd87b9bc3e78bfb01ea9ae85a40449bbcd7f3f474739ae35eb874"}}