{"id":"W4294975841","doi":"10.1109/iri54793.2022.00069","title":"Adding Explainability to Machine Learning Models to Detect Chronic Kidney Disease","year":2022,"lang":"en","type":"article","venue":"","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Kidney disease; Interpretability; Renal function; Medicine; Intensive care medicine; Disease; Machine learning; Random forest; Renal replacement therapy; Stage (stratigraphy); Computer science; Internal medicine; 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":[0.002008171,0.0005857481,0.0004650634,0.001220517,0.0002954181,0.0006889294,0.0005539107,0.0006280293,0.0007424389],"category_scores_gemma":[0.007856654,0.0001706393,0.0008728003,0.000530182,0.0003159733,0.0008500812,0.000586769,0.0008578144,0.0001457267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005567492,"about_ca_system_score_gemma":0.0005771057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006327441,"about_ca_topic_score_gemma":0.005054734,"domain_scores_codex":[0.999204,0.0003350543,0.00006273883,0.0001539996,0.000180909,0.00006333066],"domain_scores_gemma":[0.9961112,0.002968204,0.0002665185,0.0002050466,0.0003931787,0.00005591525],"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":[0.0001868868,0.0002094527,0.05847224,0.00009159468,0.0003387189,0.0002466323,0.0002231052,0.7838022,0.003094809,0.005408564,0.0009386005,0.1469872],"study_design_scores_gemma":[0.000004549706,0.00004592337,0.003323748,0.000008475669,0.00002069634,0.00003042946,0.00001262678,0.9926642,0.0004236413,0.003234677,0.0002221657,0.000008929018],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2153703,0.0005165618,0.7812221,0.0005698134,0.00004021953,0.00009162741,0.0003547597,0.0007770805,0.00105764],"genre_scores_gemma":[0.9167246,0.0001951567,0.08188441,0.00007832519,0.00003501583,0.000068847,0.0004560321,0.00002917118,0.0005286104],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006327441,"threshold_uncertainty_score":0.01258123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.19028713375368,"score_gpt":0.4549462510061526,"score_spread":0.2646591172524726,"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."}}