{"id":"W4294349358","doi":"10.2196/39143","title":"Improving Skin Color Diversity in Cancer Detection: Deep Learning Approach","year":2022,"lang":"en","type":"article","venue":"JMIR Dermatology","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Skin cancer; Deep learning; Convolutional neural network; Artificial intelligence; Dermatology; Medicine; Skin color; Skin lesion; Computer science; Cancer; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001042975,0.0005811839,0.0004298085,0.001177663,0.0002332915,0.000533833,0.0007344637,0.0006784784,0.0008824306],"category_scores_gemma":[0.001536611,0.0002696218,0.0007572086,0.0005512559,0.0002887636,0.0005926868,0.0007075315,0.0008768164,0.0002728415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008544966,"about_ca_system_score_gemma":0.0004629797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00368122,"about_ca_topic_score_gemma":0.005072391,"domain_scores_codex":[0.9996578,0.00007396426,0.00001597618,0.0001008249,0.00008587027,0.00006556877],"domain_scores_gemma":[0.9993692,0.0002304623,0.00007585432,0.00006591299,0.0002085834,0.00004995675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003064339,0.0003806037,0.01523837,0.0001464946,0.0001864628,0.0001676372,0.0001481779,0.3221242,0.03759275,0.001284103,0.00339442,0.6190304],"study_design_scores_gemma":[0.000007438177,0.00007357191,0.002610539,0.00001322701,0.00003352951,0.00008590122,0.00002236115,0.9873434,0.008082609,0.001136762,0.0005813227,0.000009218313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3287686,0.001742224,0.6626824,0.0008097889,0.0001123413,0.0001467684,0.0004120533,0.001668485,0.003657472],"genre_scores_gemma":[0.880817,0.0004283817,0.1159448,0.0003215417,0.00005620704,0.00004931082,0.0004203444,0.00006432724,0.001898152],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00368122,"threshold_uncertainty_score":0.00731957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01585753632189033,"score_gpt":0.2561114650260886,"score_spread":0.2402539287041983,"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."}}