{"id":"W4312177713","doi":"10.18280/ria.360519","title":"DermICNet: Efficient Dermoscopic Image Classification Network for Automated Skin Cancer Diagnosis","year":2022,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Softmax function; Artificial intelligence; Convolutional neural network; Computer science; Pattern recognition (psychology); Classifier (UML); Contextual image classification; Deep learning; Image (mathematics)","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":[0.0003838867,0.0004231988,0.00027525,0.0005823807,0.0002240016,0.0003324214,0.0006923978,0.0005344534,0.002036319],"category_scores_gemma":[0.0007075479,0.0001966992,0.0002532056,0.0002836856,0.0001676524,0.0004974963,0.000418854,0.0003882822,0.0004831734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008185902,"about_ca_system_score_gemma":0.0005774395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006369141,"about_ca_topic_score_gemma":0.00961267,"domain_scores_codex":[0.9998465,0.00002302919,0.000008456393,0.00004412519,0.00005508768,0.00002278536],"domain_scores_gemma":[0.9998348,0.00004352095,0.00002205747,0.0000191301,0.00006709378,0.00001335858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000704861,0.0004913759,0.009802073,0.0001763417,0.0001465242,0.0003100766,0.0000608673,0.1910078,0.04652551,0.002666662,0.01647321,0.7316347],"study_design_scores_gemma":[0.00001290715,0.00008031794,0.001717493,0.000007699972,0.00001467845,0.00009896908,0.00001023804,0.9862012,0.009582794,0.0006041778,0.001662595,0.000006877203],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2398375,0.00201978,0.7401648,0.0008718497,0.0003137312,0.000377225,0.001182277,0.008009838,0.007223006],"genre_scores_gemma":[0.8174099,0.0005170529,0.1709831,0.0003645894,0.00007505102,0.0001913956,0.001557726,0.00007515243,0.008826056],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006369141,"threshold_uncertainty_score":0.01266414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03855964644797761,"score_gpt":0.3114512622889204,"score_spread":0.2728916158409428,"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."}}