{"id":"W2998499297","doi":"","title":"Comparative Analysis of Features Selection Techniques for Classification in Healthcare.","year":2019,"lang":"en","type":"article","venue":"Machine Learning and Data Mining in Pattern Recognition","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Purdue Pharma (Canada)","funders":"","keywords":"Computer science; Selection (genetic algorithm); Health care; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"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":[0.004030914,0.0005354551,0.0007996339,0.003130486,0.0003370437,0.0008793863,0.0005195707,0.0004368688,0.002464819],"category_scores_gemma":[0.01004518,0.0001213815,0.001031245,0.002516405,0.0001961127,0.0008378314,0.0004066409,0.0003503457,0.0006429263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003908249,"about_ca_system_score_gemma":0.000554625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001929643,"about_ca_topic_score_gemma":0.002005259,"domain_scores_codex":[0.9979374,0.0008104128,0.0002075441,0.0001817279,0.0007147437,0.0001480899],"domain_scores_gemma":[0.9906724,0.007227492,0.0002864266,0.0003147041,0.001385314,0.0001137123],"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":[0.002302087,0.0003139065,0.03023004,0.000515273,0.0005712023,0.0001284466,0.0001522682,0.0101772,0.005412211,0.001207578,0.006564902,0.942425],"study_design_scores_gemma":[0.0007029253,0.006802326,0.3039722,0.0007002524,0.003613014,0.002317429,0.00208339,0.5916046,0.0437259,0.01110169,0.03318954,0.0001867251],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6637272,0.04679095,0.2676308,0.002438516,0.0007280126,0.0005253929,0.00318401,0.001534571,0.01344063],"genre_scores_gemma":[0.8987637,0.00553502,0.09000733,0.0001896242,0.0002240638,0.0001752984,0.002550429,0.00009934515,0.002455251],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004030914,"threshold_uncertainty_score":0.02131778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2409741547271774,"score_gpt":0.5102778579546496,"score_spread":0.2693037032274722,"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."}}