{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:SIGUQGS23FNWAR7ICTAQHBBEY4","short_pith_number":"pith:SIGUQGS2","schema_version":"1.0","canonical_sha256":"920d481a5ad95b6047e814c1038424c70dd3559b38c72aa15de6e58c04ce0806","source":{"kind":"arxiv","id":"2507.19803","version":1},"attestation_state":"computed","paper":{"title":"AI-Based Clinical Rule Discovery for NMIBC Recurrence through Tsetlin Machines","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Kabita Adhikari, Naeem Soomro, Rakesh Heer, Rishad Shafik, Saram Abbas","submitted_at":"2025-07-26T05:32:13Z","abstract_excerpt":"Bladder cancer claims one life every 3 minutes worldwide. Most patients are diagnosed with non-muscle-invasive bladder cancer (NMIBC), yet up to 70% recur after treatment, triggering a relentless cycle of surgeries, monitoring, and risk of progression. Clinical tools like the EORTC risk tables are outdated and unreliable - especially for intermediate-risk cases.\n  We propose an interpretable AI model using the Tsetlin Machine (TM), a symbolic learner that outputs transparent, human-readable logic. Tested on the PHOTO trial dataset (n=330), TM achieved an F1-score of 0.80, outperforming XGBoost"},"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":"2507.19803","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-26T05:32:13Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"3535d2df1b2762b61afd1bfb6a85c47151761462a9060b40d3e9e7d53d54e572","abstract_canon_sha256":"3b89103f2a6e27371ae895d2558d26c2623ff9d755346dc2f89764c262dd4185"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:43:42.308306Z","signature_b64":"uFMZsfIy+4udOEAt/ZFzstcrLcPd61Zqh4+ikQka3wyLTk1uHlqohn8C+zjrFlzk8lceq3UzyKv45oEefoYSAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"920d481a5ad95b6047e814c1038424c70dd3559b38c72aa15de6e58c04ce0806","last_reissued_at":"2026-07-05T11:43:42.307861Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:43:42.307861Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"AI-Based Clinical Rule Discovery for NMIBC Recurrence through Tsetlin Machines","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Kabita Adhikari, Naeem Soomro, Rakesh Heer, Rishad Shafik, Saram Abbas","submitted_at":"2025-07-26T05:32:13Z","abstract_excerpt":"Bladder cancer claims one life every 3 minutes worldwide. Most patients are diagnosed with non-muscle-invasive bladder cancer (NMIBC), yet up to 70% recur after treatment, triggering a relentless cycle of surgeries, monitoring, and risk of progression. Clinical tools like the EORTC risk tables are outdated and unreliable - especially for intermediate-risk cases.\n  We propose an interpretable AI model using the Tsetlin Machine (TM), a symbolic learner that outputs transparent, human-readable logic. Tested on the PHOTO trial dataset (n=330), TM achieved an F1-score of 0.80, outperforming XGBoost"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.19803","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2507.19803/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2507.19803","created_at":"2026-07-05T11:43:42.307924+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.19803v1","created_at":"2026-07-05T11:43:42.307924+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.19803","created_at":"2026-07-05T11:43:42.307924+00:00"},{"alias_kind":"pith_short_12","alias_value":"SIGUQGS23FNW","created_at":"2026-07-05T11:43:42.307924+00:00"},{"alias_kind":"pith_short_16","alias_value":"SIGUQGS23FNWAR7I","created_at":"2026-07-05T11:43:42.307924+00:00"},{"alias_kind":"pith_short_8","alias_value":"SIGUQGS2","created_at":"2026-07-05T11:43:42.307924+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/SIGUQGS23FNWAR7ICTAQHBBEY4","json":"https://pith.science/pith/SIGUQGS23FNWAR7ICTAQHBBEY4.json","graph_json":"https://pith.science/api/pith-number/SIGUQGS23FNWAR7ICTAQHBBEY4/graph.json","events_json":"https://pith.science/api/pith-number/SIGUQGS23FNWAR7ICTAQHBBEY4/events.json","paper":"https://pith.science/paper/SIGUQGS2"},"agent_actions":{"view_html":"https://pith.science/pith/SIGUQGS23FNWAR7ICTAQHBBEY4","download_json":"https://pith.science/pith/SIGUQGS23FNWAR7ICTAQHBBEY4.json","view_paper":"https://pith.science/paper/SIGUQGS2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.19803&json=true","fetch_graph":"https://pith.science/api/pith-number/SIGUQGS23FNWAR7ICTAQHBBEY4/graph.json","fetch_events":"https://pith.science/api/pith-number/SIGUQGS23FNWAR7ICTAQHBBEY4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SIGUQGS23FNWAR7ICTAQHBBEY4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SIGUQGS23FNWAR7ICTAQHBBEY4/action/storage_attestation","attest_author":"https://pith.science/pith/SIGUQGS23FNWAR7ICTAQHBBEY4/action/author_attestation","sign_citation":"https://pith.science/pith/SIGUQGS23FNWAR7ICTAQHBBEY4/action/citation_signature","submit_replication":"https://pith.science/pith/SIGUQGS23FNWAR7ICTAQHBBEY4/action/replication_record"}},"created_at":"2026-07-05T11:43:42.307924+00:00","updated_at":"2026-07-05T11:43:42.307924+00:00"}