{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002585961,0.0001219616,0.0001768891,0.0003050755,0.00120645,0.0000126557,0.00005159221,0.0001555558,0.00001076571],"category_scores_gemma":[0.00001684882,0.00009489562,0.00001136862,0.0002512544,0.00002511634,0.0001541265,0.0001006408,0.0004049462,0.000001185304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004093116,"about_ca_system_score_gemma":0.0002364742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002388514,"about_ca_topic_score_gemma":0.0000703583,"domain_scores_codex":[0.9988798,0.00007052495,0.0004908309,0.000138942,0.0001455121,0.0002743264],"domain_scores_gemma":[0.9995835,0.00002090652,0.0001986047,0.0001068828,0.00005588747,0.0000341631],"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":[0.00005221797,0.0001520828,0.2561762,0.00005395943,0.00001584056,2.024973e-7,0.006568972,0.7140999,0.00005046632,0.0005168784,0.000004219292,0.02230912],"study_design_scores_gemma":[0.001399079,0.0003140509,0.002986322,0.00004062357,0.000006589203,2.461445e-7,0.0008358823,0.9940491,0.0000184715,0.00002064241,0.0002271396,0.0001018719],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9465094,0.00001669305,0.05180496,0.0004506503,0.00003457254,0.001012834,0.00003410703,0.00008383321,0.00005297795],"genre_scores_gemma":[0.922491,0.00001600402,0.07663532,0.00008184541,0.000005604408,0.0003251057,0.0003469644,0.00001305799,0.00008512889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2799492,"threshold_uncertainty_score":0.9279156,"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."}}