{"id":"W4378187052","doi":"10.18280/ria.370226","title":"Prediction of Chronic Kidney Disease with Machine Learning Models and Feature Analysis Using SHAP","year":2023,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Feature (linguistics); Kidney disease; Artificial intelligence; Computer science; Medicine; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008934565,0.0002509346,0.0004827445,0.0005844585,0.0009752055,0.00001798298,0.0002241003,0.0002082814,0.0004010862],"category_scores_gemma":[0.0003557537,0.0002222318,0.0001306322,0.002830829,0.0002110055,0.0002675948,0.0001311983,0.0008397892,0.000125672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002165327,"about_ca_system_score_gemma":0.0004045252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001000619,"about_ca_topic_score_gemma":0.0006088426,"domain_scores_codex":[0.9971631,0.000387027,0.0008175531,0.0006135507,0.0003416142,0.0006771443],"domain_scores_gemma":[0.9977213,0.0004843404,0.0003965461,0.0005410573,0.0003831673,0.0004736434],"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":[0.0001620505,0.00005415616,0.183837,0.0009581698,0.0001543441,0.00002157855,0.007343277,0.8014545,0.001169681,0.001615938,0.0002161841,0.003013112],"study_design_scores_gemma":[0.00004029265,0.0001495229,0.001055713,0.0006301461,0.0002962407,0.000002031718,0.004791541,0.9898189,0.0009009484,0.001166903,0.0009661426,0.0001815719],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8618553,0.001611098,0.1311557,0.00201609,0.0004628099,0.001451452,0.0003640554,0.0004599757,0.0006234437],"genre_scores_gemma":[0.9956881,0.0008980723,0.0004186088,0.0001077237,0.00020887,0.00007550992,0.0001917718,0.00004977197,0.002361534],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1883644,"threshold_uncertainty_score":0.9062349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1961365130582876,"score_gpt":0.4097559467544276,"score_spread":0.21361943369614,"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."}}