{"id":"W4353100312","doi":"10.18280/ts.400128","title":"SkinCancerNet: Automated Classification of Skin Lesion Using Deep Transfer Learning Method","year":2023,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transfer of learning; Artificial intelligence; Computer science; Lesion; Pattern recognition (psychology); Skin lesion; Deep learning; Transfer (computing); Medicine; Dermatology; 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":[0.0004571189,0.001101767,0.0005270776,0.001697229,0.0002570376,0.0004839911,0.00102147,0.0008356638,0.004080302],"category_scores_gemma":[0.0006746015,0.0002558651,0.0006080284,0.0006717149,0.000162775,0.0006344794,0.0006338774,0.0006164851,0.001612829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006900389,"about_ca_system_score_gemma":0.0007468018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007575133,"about_ca_topic_score_gemma":0.008806042,"domain_scores_codex":[0.9997405,0.00003356493,0.00001569961,0.00008761586,0.00007388078,0.00004861123],"domain_scores_gemma":[0.9998602,0.0000243327,0.00001728687,0.00002506656,0.00005820541,0.00001496522],"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":[0.0007494969,0.0008068074,0.01630175,0.0004869617,0.0003110217,0.0005106433,0.00008079943,0.07443093,0.04594342,0.00169179,0.05414738,0.804539],"study_design_scores_gemma":[0.00004561942,0.0002432285,0.005778491,0.00003414036,0.00004026975,0.000334644,0.00003940712,0.9576594,0.02838778,0.001195399,0.006213958,0.0000276528],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3979169,0.004636526,0.5260633,0.0006455215,0.0007257191,0.001070731,0.01115051,0.04548674,0.01230401],"genre_scores_gemma":[0.7815954,0.000979619,0.1768745,0.0003699581,0.0001248288,0.0005333607,0.02278528,0.0004440075,0.01629308],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007575133,"threshold_uncertainty_score":0.01506209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0528926410035158,"score_gpt":0.3309256096892396,"score_spread":0.2780329686857238,"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."}}