{"id":"W4382395279","doi":"10.18280/ts.400330","title":"Deep Learning-Based Dermoscopic Image Classification System for Robust Skin Lesion Analysis","year":2023,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Skin lesion; Pattern recognition (psychology); Computer science; Deep learning; Lesion; Image (mathematics); Contextual image classification; Computer vision; Dermatology; Medicine; Pathology","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":[0.0004405805,0.000469494,0.0005556327,0.001069631,0.0002219334,0.0005310094,0.0007667069,0.0005948557,0.003156329],"category_scores_gemma":[0.0008214172,0.0002118619,0.0003961546,0.0004564847,0.0001780625,0.0005128261,0.0006126834,0.0006143745,0.001362962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006011078,"about_ca_system_score_gemma":0.000498249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002426407,"about_ca_topic_score_gemma":0.004201791,"domain_scores_codex":[0.9996934,0.00003085993,0.00002250259,0.00009164667,0.0001209985,0.00004062742],"domain_scores_gemma":[0.9996544,0.00005730696,0.00004668626,0.00005386737,0.0001571606,0.00003055194],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003673465,0.0003000555,0.00667099,0.0001762055,0.00008819099,0.0002973971,0.00005777543,0.02615408,0.1113471,0.001318991,0.009986181,0.8432357],"study_design_scores_gemma":[0.00002162551,0.0001423916,0.006891239,0.00002371963,0.00004854741,0.0004667132,0.00002630631,0.9373928,0.04847974,0.0012588,0.00522036,0.00002767864],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07380289,0.000746238,0.9123059,0.000396606,0.0001245294,0.0002668548,0.0007652288,0.00781198,0.003779852],"genre_scores_gemma":[0.5822144,0.0005813673,0.4040315,0.0005235908,0.0001146896,0.0002799823,0.001754317,0.0001960683,0.01030407],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003156329,"threshold_uncertainty_score":0.01055896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03483330070226205,"score_gpt":0.2745979456833344,"score_spread":0.2397646449810724,"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."}}