{"id":"W4253451986","doi":"10.1055/s-0039-1681086","title":"Analysis of Machine Learning Algorithms for Diagnosis of Diffuse Lung Diseases","year":2018,"lang":"en","type":"article","venue":"Methods of Information in Medicine","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Artificial intelligence; Dimensionality reduction; Feature selection; Computer science; Linear discriminant analysis; Convolutional neural network; Pattern recognition (psychology); Support vector machine; Machine learning; CAD; Computer-aided diagnosis; Principal component analysis; Artificial neural network; Feature (linguistics); Algorithm","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":[0.002265664,0.0008183534,0.0008482254,0.002016178,0.0003449185,0.001114939,0.0006111009,0.0008317754,0.001603207],"category_scores_gemma":[0.00639719,0.0002321056,0.0008219014,0.001096853,0.0003414072,0.0006477929,0.0004848232,0.0007341831,0.0003578195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009773904,"about_ca_system_score_gemma":0.0009668436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003405246,"about_ca_topic_score_gemma":0.001816774,"domain_scores_codex":[0.9991719,0.0003090047,0.00006674288,0.0001282409,0.0002688443,0.00005542062],"domain_scores_gemma":[0.9974731,0.00179822,0.00014925,0.0001075555,0.000436774,0.00003512797],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001079484,0.00009506932,0.003553181,0.0001864807,0.0001315718,0.00005919946,0.00004825632,0.6645257,0.001798572,0.009402947,0.001922859,0.3181682],"study_design_scores_gemma":[0.000003685178,0.00002142821,0.0005469031,0.000009901109,0.000008118413,0.00001456143,0.000006897857,0.9964004,0.0003681305,0.002222329,0.0003946853,0.000002955101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04606122,0.005163796,0.94282,0.0006523418,0.0001121285,0.0001171909,0.000148268,0.0005773802,0.004347722],"genre_scores_gemma":[0.6222905,0.002603863,0.3705785,0.0001941066,0.0001460198,0.0002873147,0.000472532,0.0001271746,0.00330009],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003405246,"threshold_uncertainty_score":0.01198208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02911482892497285,"score_gpt":0.4137046853073567,"score_spread":0.3845898563823838,"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."}}