{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:W3EUNFZYWSG4GLRE435UO4BNVE","short_pith_number":"pith:W3EUNFZY","schema_version":"1.0","canonical_sha256":"b6c9469738b48dc32e24e6fb47702da92957d2a3ad2d16d1f4b426a23132e095","source":{"kind":"arxiv","id":"1511.03361","version":1},"attestation_state":"computed","paper":{"title":"Discovery Radiomics via StochasticNet Sequencers for Cancer Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Alexander Wong, Audrey G. Chung, Devinder Kumar, Farzad Khalvati, Masoom Haider, Mohammad Javad Shafiee","submitted_at":"2015-11-11T02:27:23Z","abstract_excerpt":"Radiomics has proven to be a powerful prognostic tool for cancer detection, and has previously been applied in lung, breast, prostate, and head-and-neck cancer studies with great success. However, these radiomics-driven methods rely on pre-defined, hand-crafted radiomic feature sets that can limit their ability to characterize unique cancer traits. In this study, we introduce a novel discovery radiomics framework where we directly discover custom radiomic features from the wealth of available medical imaging data. In particular, we leverage novel StochasticNet radiomic sequencers for extractin"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1511.03361","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-11-11T02:27:23Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"7d49c2ec3061e18a3225321f3a5f3838d785d4643cc17a501d2c4b0016d263fe","abstract_canon_sha256":"490ed18e66a73323a8faee55df36537279cb4891b1fa208c1a3163dad012c2da"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:27:15.637165Z","signature_b64":"+fJUE9swQh6Cd2+YaUbcZhwgublWOmDLoblgVUQ4TcW0fZKpeZdKjjqSXdRg0HvER/ZFsZooAKbiAaKuQDSiDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b6c9469738b48dc32e24e6fb47702da92957d2a3ad2d16d1f4b426a23132e095","last_reissued_at":"2026-05-18T01:27:15.636412Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:27:15.636412Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Discovery Radiomics via StochasticNet Sequencers for Cancer Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Alexander Wong, Audrey G. Chung, Devinder Kumar, Farzad Khalvati, Masoom Haider, Mohammad Javad Shafiee","submitted_at":"2015-11-11T02:27:23Z","abstract_excerpt":"Radiomics has proven to be a powerful prognostic tool for cancer detection, and has previously been applied in lung, breast, prostate, and head-and-neck cancer studies with great success. However, these radiomics-driven methods rely on pre-defined, hand-crafted radiomic feature sets that can limit their ability to characterize unique cancer traits. In this study, we introduce a novel discovery radiomics framework where we directly discover custom radiomic features from the wealth of available medical imaging data. In particular, we leverage novel StochasticNet radiomic sequencers for extractin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1511.03361","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1511.03361","created_at":"2026-05-18T01:27:15.636531+00:00"},{"alias_kind":"arxiv_version","alias_value":"1511.03361v1","created_at":"2026-05-18T01:27:15.636531+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1511.03361","created_at":"2026-05-18T01:27:15.636531+00:00"},{"alias_kind":"pith_short_12","alias_value":"W3EUNFZYWSG4","created_at":"2026-05-18T12:29:47.479230+00:00"},{"alias_kind":"pith_short_16","alias_value":"W3EUNFZYWSG4GLRE","created_at":"2026-05-18T12:29:47.479230+00:00"},{"alias_kind":"pith_short_8","alias_value":"W3EUNFZY","created_at":"2026-05-18T12:29:47.479230+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/W3EUNFZYWSG4GLRE435UO4BNVE","json":"https://pith.science/pith/W3EUNFZYWSG4GLRE435UO4BNVE.json","graph_json":"https://pith.science/api/pith-number/W3EUNFZYWSG4GLRE435UO4BNVE/graph.json","events_json":"https://pith.science/api/pith-number/W3EUNFZYWSG4GLRE435UO4BNVE/events.json","paper":"https://pith.science/paper/W3EUNFZY"},"agent_actions":{"view_html":"https://pith.science/pith/W3EUNFZYWSG4GLRE435UO4BNVE","download_json":"https://pith.science/pith/W3EUNFZYWSG4GLRE435UO4BNVE.json","view_paper":"https://pith.science/paper/W3EUNFZY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1511.03361&json=true","fetch_graph":"https://pith.science/api/pith-number/W3EUNFZYWSG4GLRE435UO4BNVE/graph.json","fetch_events":"https://pith.science/api/pith-number/W3EUNFZYWSG4GLRE435UO4BNVE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/W3EUNFZYWSG4GLRE435UO4BNVE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/W3EUNFZYWSG4GLRE435UO4BNVE/action/storage_attestation","attest_author":"https://pith.science/pith/W3EUNFZYWSG4GLRE435UO4BNVE/action/author_attestation","sign_citation":"https://pith.science/pith/W3EUNFZYWSG4GLRE435UO4BNVE/action/citation_signature","submit_replication":"https://pith.science/pith/W3EUNFZYWSG4GLRE435UO4BNVE/action/replication_record"}},"created_at":"2026-05-18T01:27:15.636531+00:00","updated_at":"2026-05-18T01:27:15.636531+00:00"}