{"id":"W3014648932","doi":"10.1088/1361-6560/ab86d3","title":"Melanoma detection using adversarial training and deep transfer learning","year":2020,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transfer of learning; Convolutional neural network; Deep learning; Classifier (UML); Leverage (statistics); Pattern recognition (psychology); Skin lesion; Contextual image classification; Visualization","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001085957,0.00009711162,0.0002726248,0.00005502849,0.0000551962,0.000003321404,0.00001747505,0.00006363825,0.00002606951],"category_scores_gemma":[0.00006614655,0.0000779792,0.00001979675,0.0001334422,0.0001105247,0.00002389412,0.00001863302,0.0002281826,0.000001062549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001573053,"about_ca_system_score_gemma":0.000009804906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007008712,"about_ca_topic_score_gemma":0.00002373313,"domain_scores_codex":[0.9994016,0.00004876846,0.0001514668,0.0002131895,0.00004699953,0.000137993],"domain_scores_gemma":[0.999787,0.00005084001,0.00002143044,0.00003906964,0.00001510304,0.00008657498],"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":[0.0006127398,0.0000358929,0.008819352,0.0001370279,0.0001075532,0.00008156835,0.01064742,0.0001433935,0.2945423,0.001388036,0.000006690339,0.6834781],"study_design_scores_gemma":[0.05170174,0.03073223,0.02079749,0.0008601528,0.002188607,0.002774076,0.06731941,0.645394,0.01884165,0.009017278,0.1483318,0.002041562],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9705853,0.0003143952,0.02630635,0.001492247,0.0001591429,0.0001718836,3.754137e-7,0.00003742325,0.0009329164],"genre_scores_gemma":[0.9977396,0.0002131371,0.0001716585,0.001113901,0.0007341809,0.000003172361,0.000005649462,0.000008799409,0.000009969671],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6814365,"threshold_uncertainty_score":0.3179899,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1917215895786067,"score_gpt":0.3447852051825651,"score_spread":0.1530636156039584,"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."}}