{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004426735,0.0001283046,0.0002298621,0.0002825479,0.00008868609,0.00001332258,0.00005521619,0.00006482092,0.0008824038],"category_scores_gemma":[0.00001345106,0.0001207529,0.0001054189,0.0004735537,0.00002711897,0.0000445099,0.00001730773,0.0001200531,0.00004259295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009896992,"about_ca_system_score_gemma":0.00003195617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007032719,"about_ca_topic_score_gemma":0.00001456783,"domain_scores_codex":[0.9987325,0.0001066296,0.0003591939,0.0002388618,0.0003585262,0.000204288],"domain_scores_gemma":[0.9996206,0.00005094891,0.00007017795,0.0001156181,0.00006915547,0.00007349725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004369829,0.0002036519,0.000977391,0.000309024,0.0002052269,0.0000618577,0.00142439,0.02847297,0.8466076,0.0007056296,0.0005840279,0.1200113],"study_design_scores_gemma":[0.001593711,0.0003932823,0.04132722,0.0001064827,0.0002010761,0.00005408065,0.001013773,0.9217656,0.0258648,0.00002436259,0.007504555,0.0001510313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8729901,0.00003009426,0.1238211,0.0002438585,0.0001265465,0.0005268641,0.000002905228,0.0006497505,0.001608761],"genre_scores_gemma":[0.9969242,0.00002793988,0.00233144,0.00006994199,0.0000994539,0.00002128744,0.00005391914,0.00002716236,0.0004446912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8932927,"threshold_uncertainty_score":0.9661703,"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."}}