{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:CKCEM446AEW2SPHUWX7I2BCTNT","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":"d57544a8078183847894d8fea313a3f40a716c2bdb8814c958a8da4f6eb480fe","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2025-02-14T16:58:30Z","title_canon_sha256":"839659ed6d8ecceb8f9d1b33ade5e106d33fa6f74994afb71f5edb030126d093"},"schema_version":"1.0","source":{"id":"2502.10296","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.10296","created_at":"2026-07-05T10:14:31Z"},{"alias_kind":"arxiv_version","alias_value":"2502.10296v1","created_at":"2026-07-05T10:14:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.10296","created_at":"2026-07-05T10:14:31Z"},{"alias_kind":"pith_short_12","alias_value":"CKCEM446AEW2","created_at":"2026-07-05T10:14:31Z"},{"alias_kind":"pith_short_16","alias_value":"CKCEM446AEW2SPHU","created_at":"2026-07-05T10:14:31Z"},{"alias_kind":"pith_short_8","alias_value":"CKCEM446","created_at":"2026-07-05T10:14:31Z"}],"graph_snapshots":[{"event_id":"sha256:f1761c06c79bb7bf225a12c00206668728bdd06356afad52650ae7eb112ee3c5","target":"graph","created_at":"2026-07-05T10:14:31Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2502.10296/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning-based medical image analysis faces a significant barrier due to the lack of interpretability. Conventional explainable AI (XAI) techniques, such as Grad-CAM and SHAP, often highlight regions outside clinical interests. To address this issue, we propose Segmentation-based Explanation (SegX), a plug-and-play approach that enhances interpretability by aligning the model's explanation map with clinically relevant areas leveraging the power of segmentation models. Furthermore, we introduce Segmentation-based Uncertainty Assessment (SegU), a method to quantify the uncertainty of the pr","authors_text":"Mingcheng Zhu, Yuhao Zhang, Zhiyao Luo","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2025-02-14T16:58:30Z","title":"SegX: Improving Interpretability of Clinical Image Diagnosis with Segmentation-based Enhancement"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.10296","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":"sha256:4a2d692869c405344aaea16f1e1474a4a29e3215c4203b6032ac59e841f51974","target":"record","created_at":"2026-07-05T10:14:31Z","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":"d57544a8078183847894d8fea313a3f40a716c2bdb8814c958a8da4f6eb480fe","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2025-02-14T16:58:30Z","title_canon_sha256":"839659ed6d8ecceb8f9d1b33ade5e106d33fa6f74994afb71f5edb030126d093"},"schema_version":"1.0","source":{"id":"2502.10296","kind":"arxiv","version":1}},"canonical_sha256":"128446739e012da93cf4b5fe8d04536cf8aa8bfbcb7a587d87d47e004f6c8fed","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"128446739e012da93cf4b5fe8d04536cf8aa8bfbcb7a587d87d47e004f6c8fed","first_computed_at":"2026-07-05T10:14:31.290888Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:14:31.290888Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Bk9x54SegKbIvK7T/7Y8eLb5ouIvUPqf9MT4HILi3/vEphUUDJKgVBYvGTd6dc/ZONQlYUoufTQZ1Q5id+UiAg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:14:31.291473Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.10296","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4a2d692869c405344aaea16f1e1474a4a29e3215c4203b6032ac59e841f51974","sha256:f1761c06c79bb7bf225a12c00206668728bdd06356afad52650ae7eb112ee3c5"],"state_sha256":"88bcc1d164ce6f275e7aba6f527fd5775004a090fa299ec2c20bba68cc118e02"}