{"id":"W4391858226","doi":"10.2196/52674","title":"Importance of Patient History in Artificial Intelligence–Assisted Medical Diagnosis: Comparison Study","year":2024,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medical diagnosis; Medical history; Medicine; Physical examination; Clinical history; Clinical diagnosis; Medical record; Past medical history; Diagnostic accuracy; Pediatrics; Surgery; Pathology; Radiology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01432078,0.0003043529,0.00058175,0.002139984,0.0005629239,0.001278562,0.0007001828,0.0008964117,0.001687441],"category_scores_gemma":[0.0903041,0.0002138627,0.0008913072,0.001342808,0.0008078857,0.002046664,0.001602915,0.0008515916,0.0002813482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001368051,"about_ca_system_score_gemma":0.001190783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002043731,"about_ca_topic_score_gemma":0.002631545,"domain_scores_codex":[0.9877217,0.007957055,0.001602438,0.0006595259,0.001814554,0.000244681],"domain_scores_gemma":[0.8726572,0.1033791,0.0107392,0.003682237,0.007124508,0.002417655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003036347,0.0006255669,0.9375384,0.0007821731,0.0004432684,0.0006541642,0.002346627,0.00048517,0.0001764115,0.0005799721,0.0005984588,0.05273348],"study_design_scores_gemma":[0.0006366767,0.007730054,0.9508004,0.001075707,0.00143792,0.007383861,0.006144958,0.01382457,0.00134986,0.001748832,0.007737821,0.0001293674],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991524,0.003492926,0.001441029,0.0004115906,0.00009981041,0.0002706603,0.0002997871,0.00001357823,0.002446726],"genre_scores_gemma":[0.9974232,0.0006483102,0.001398072,0.00009848658,0.00006269944,0.00008351491,0.0001819402,0.000003358356,0.0001005846],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01432078,"threshold_uncertainty_score":0.0757364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.145759102751727,"score_gpt":0.4781336460701806,"score_spread":0.3323745433184535,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}