{"id":"W4303444817","doi":"10.1145/3549555.3549584","title":"Skin Cancer Detection using Ensemble Learning and Grouping of Deep Models","year":2022,"lang":"en","type":"article","venue":"","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"New Brunswick Innovation Foundation; Compute Canada","keywords":"Pipeline (software); Computer science; Artificial intelligence; Convolutional neural network; Deep learning; Skin cancer; Upsampling; Machine learning; Informatics; Weighting; Contextual image classification; Pattern recognition (psychology); Image (mathematics); Cancer; Medicine; Engineering; Radiology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007849254,0.001085919,0.0009745405,0.0015424,0.0004470935,0.0006939218,0.00104548,0.0008054095,0.00111022],"category_scores_gemma":[0.001390519,0.0004312482,0.001220646,0.0006632411,0.0001910216,0.0009591436,0.001077792,0.001237585,0.0006801958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006252615,"about_ca_system_score_gemma":0.0005807044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009146119,"about_ca_topic_score_gemma":0.01266141,"domain_scores_codex":[0.9995543,0.0000787532,0.00002008443,0.0001646981,0.00009012548,0.00009194941],"domain_scores_gemma":[0.9994667,0.0001428562,0.00006099045,0.00009119821,0.0001867173,0.0000515264],"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":[0.0003143466,0.0004271055,0.02078675,0.00007878258,0.0003118635,0.0003038068,0.0001269678,0.2972871,0.01933914,0.001306674,0.008037832,0.6516798],"study_design_scores_gemma":[0.000002903186,0.00003388093,0.000967373,0.000005406978,0.00002002209,0.00002957888,0.00000920616,0.9956871,0.002095488,0.0007812132,0.0003623982,0.00000551167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2008823,0.001699072,0.7871931,0.0004955126,0.0001858786,0.0001384161,0.000646466,0.005622272,0.003136999],"genre_scores_gemma":[0.879548,0.0004290882,0.1142311,0.0002464326,0.00009613477,0.00007405497,0.001460009,0.000144337,0.003770849],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009146119,"threshold_uncertainty_score":0.01818579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02196395503072651,"score_gpt":0.2692660485208587,"score_spread":0.2473020934901322,"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."}}