{"id":"W4280614593","doi":"10.2196/37531","title":"Using Artificial Intelligence as a Diagnostic Decision Support Tool in Skin Disease: Protocol for an Observational Prospective Cohort Study","year":2022,"lang":"en","type":"article","venue":"JMIR Research Protocols","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Observational study; Skin cancer; Medicine; Protocol (science); Decision support system; Disease; Cohort study; Cohort; Skin lesion; Primary care; Health professionals; Health care; Medical physics; Teledermatology; Artificial intelligence; Family medicine; Dermatology; Computer science; Pathology; Cancer; Alternative medicine; Internal medicine","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":[0.01822714,0.002029578,0.002985712,0.001869199,0.002135347,0.001459981,0.001384002,0.002359003,0.01749353],"category_scores_gemma":[0.01334677,0.001246823,0.00258659,0.002156042,0.001577479,0.00124209,0.001323846,0.00200199,0.003031856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003224444,"about_ca_system_score_gemma":0.008627983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003127434,"about_ca_topic_score_gemma":0.003436369,"domain_scores_codex":[0.9904479,0.005208545,0.001611479,0.0009729526,0.001075096,0.0006841295],"domain_scores_gemma":[0.9912483,0.001987732,0.001380698,0.001453743,0.003165338,0.0007643058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"observational","study_design_scores_codex":[0.3899421,0.1163393,0.1877836,0.04073296,0.004570618,0.004455585,0.006868816,0.01505592,0.01026985,0.01115208,0.0582407,0.1545885],"study_design_scores_gemma":[0.1742671,0.2461741,0.3874276,0.01163504,0.002867015,0.001378679,0.007645205,0.009440721,0.004138936,0.006674568,0.147354,0.0009969315],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.03212116,0.0005270613,0.004666489,0.0001980621,0.0002133137,0.9572482,0.003591218,0.00004508784,0.001389423],"genre_scores_gemma":[0.01468059,0.0002081271,0.00310677,0.0001285443,0.00003687713,0.9804349,0.001010643,0.000004961179,0.0003885807],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.01822714,"threshold_uncertainty_score":0.09639549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4726621317253243,"score_gpt":0.5932009572704006,"score_spread":0.1205388255450763,"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."}}