{"id":"W4296896547","doi":"10.2196/37951","title":"Treatment Discontinuation Prediction in Patients With Diabetes Using a Ranking Model: Machine Learning Model Development","year":2022,"lang":"en","type":"article","venue":"JMIR Bioinformatics and Biotechnology","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Tokyo","keywords":"Medicine; Discontinuation; Diabetes mellitus; Medical record; Diagnosis code; Intervention (counseling); Ranking (information retrieval); Emergency medicine; Pediatrics; Artificial intelligence; Internal medicine; Computer science","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":[0.00423967,0.001049471,0.001239849,0.001426799,0.0004784938,0.00132735,0.001223715,0.001136991,0.001935377],"category_scores_gemma":[0.009195631,0.0004096989,0.001485758,0.0009012427,0.0003150519,0.0006211465,0.0006896204,0.00205502,0.0003799649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001383067,"about_ca_system_score_gemma":0.001618545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01901276,"about_ca_topic_score_gemma":0.01028979,"domain_scores_codex":[0.9987249,0.0006990108,0.00009462681,0.0002181074,0.0001150144,0.0001483005],"domain_scores_gemma":[0.9915263,0.006792278,0.0005314503,0.0001521533,0.0007963707,0.0002013606],"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":[0.0003442335,0.0004497551,0.06404751,0.0001079572,0.000286054,0.0002499571,0.0001169161,0.8709575,0.0002525294,0.001496909,0.002325118,0.05936562],"study_design_scores_gemma":[0.000009950162,0.00004847835,0.001292638,0.000009696752,0.00001554028,0.00001466512,0.000009711412,0.9980029,0.0000334533,0.0004662438,0.00009125267,0.000005365571],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6804778,0.002958734,0.3035412,0.00448008,0.000281571,0.000504386,0.002151625,0.0008408425,0.004763722],"genre_scores_gemma":[0.9617572,0.0005447644,0.03439163,0.0002388556,0.0001037472,0.0003033878,0.00105712,0.00002190425,0.001581405],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01901276,"threshold_uncertainty_score":0.03780419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03078617011318962,"score_gpt":0.3119124348642269,"score_spread":0.2811262647510372,"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."}}