{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001613337,0.0008476207,0.00106437,0.001925187,0.0003164411,0.001171051,0.0006021802,0.0007758407,0.00106463],"category_scores_gemma":[0.004990413,0.0002187542,0.001442266,0.001317168,0.0001717613,0.0008446819,0.0004892456,0.001084374,0.0006057096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004692609,"about_ca_system_score_gemma":0.0007336945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008024457,"about_ca_topic_score_gemma":0.003999359,"domain_scores_codex":[0.999158,0.0002328866,0.00009491437,0.0002045026,0.0002031968,0.0001065],"domain_scores_gemma":[0.9985301,0.0008851038,0.0001666969,0.00008804083,0.0002865343,0.00004358154],"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":[0.0007443134,0.0008662219,0.1437999,0.0003126487,0.0006266375,0.0004845982,0.0001202412,0.3339154,0.004457387,0.001795941,0.01045681,0.50242],"study_design_scores_gemma":[0.000009506126,0.0001180244,0.007947397,0.00003357382,0.00004845736,0.00009573316,0.00003324425,0.9891443,0.0008112036,0.001206928,0.0005332362,0.00001836964],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3968659,0.004980585,0.5858845,0.00155549,0.000513271,0.0002993144,0.003258563,0.00309766,0.003544726],"genre_scores_gemma":[0.939357,0.0008360427,0.05597423,0.0001293074,0.0001761382,0.0001320117,0.002294323,0.00003151623,0.001069426],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008024457,"threshold_uncertainty_score":0.01595551,"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."}}