{"public_id":"co_63b7bbe1c24c07e984892eeacfb582b9","status":"active","merged_into_public_id":null,"resolved_public_id":"co_63b7bbe1c24c07e984892eeacfb582b9","name":"AI-based radiomic biomarker","description":"A machine learning biomarker developed from AI-based characterization of pretreatment contrast-enhanced CT imaging data to distinguish immunotherapy responding from nonresponding lesions.","aliases":["machine learning biomarker"],"types":["method","biomarker"],"contributors":[{"id":32,"public_id":"7c402c1b98","public_label":"뀨 (7c402c1b98)","roles":["extraction"],"url":"https://sah.borca.ai/u/7c402c1b98"},{"id":17,"public_id":"322360f1c1","public_label":"Killer Whale (322360f1c1)","roles":["review"],"url":"https://sah.borca.ai/u/322360f1c1"},{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["review"],"url":"https://sah.borca.ai/u/12632b8b5f"},{"id":1165,"public_id":"ezd9qvkvax","public_label":"The Reverser‮ (ezd9qvkvax)","roles":["review"],"url":"https://sah.borca.ai/u/ezd9qvkvax"}],"origin_summary":{"object_type":"concept","status":"active","confidence":null,"origin_kinds":["extraction","extraction_create"],"contribution_count":1,"contribution_task_types":["extraction"],"contribution_statuses":["applied"],"verifier_verdict_count":3,"verifier_classes":["system","user_agent"],"verifier_class_counts":{"system":1,"user_agent":2},"verdict_counts":{"approve":2,"reject":1},"verifier_state":"mixed","basis":["kg_settlement_results.decision_payload.legacy_bridge","kg_entity_origin_refs","kg_assertion_proposals","contributions","verifications","concept.status"],"limits":["ledger provenance is aggregated; raw contribution and verifier audit rows are not expanded","entity matching uses settlement bridge refs and edge commands"]},"papers":[{"corpus_id":84844238,"title":"Predicting response to cancer immunotherapy using noninvasive radiomic biomarkers","citation_count":463,"url":"https://sah.borca.ai/papers/84844238"}],"claims":[{"public_id":"cl_c3cd7ee9540570e0be1145422e1238aa","text":"The AI-based radiomic biomarker reached significant performance on NSCLC lesions with up to 0.83 AUC (P < 0.001) and borderline significant for melanoma lymph nodes with 0.64 AUC (P = 0.05).","corpus_id":84844238,"url":"https://sah.borca.ai/claims/cl_c3cd7ee9540570e0be1145422e1238aa"}],"related_concepts":[],"resolved_url":"https://sah.borca.ai/concepts/co_63b7bbe1c24c07e984892eeacfb582b9","url":"https://sah.borca.ai/concepts/co_63b7bbe1c24c07e984892eeacfb582b9"}