{"id":"W3125832735","doi":"10.2196/22148","title":"Machine Learning Approach to Decision Making for Insulin Initiation in Japanese Patients With Type 2 Diabetes (JDDM 58): Model Development and Validation Study","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Hyperglycemia and glycemic control in critically ill and hospitalized patients","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Japan Society for the Promotion of Science","keywords":"Machine learning; Logistic regression; Artificial intelligence; Receiver operating characteristic; Gold standard (test); Medicine; Diabetes mellitus; F1 score; Insulin; Artificial neural network; Computer science; Internal medicine; Endocrinology","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":[0.01119728,0.001080939,0.001098305,0.001163315,0.000600654,0.0009640005,0.0009469823,0.0006707624,0.00130564],"category_scores_gemma":[0.01852268,0.000336347,0.001794498,0.0008925407,0.0004209465,0.0005003079,0.0009693377,0.001177417,0.0002437984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001480999,"about_ca_system_score_gemma":0.002412778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03360594,"about_ca_topic_score_gemma":0.01323042,"domain_scores_codex":[0.997885,0.00132314,0.0001327592,0.0002946774,0.000181165,0.0001831625],"domain_scores_gemma":[0.9850752,0.01151847,0.0007221866,0.000687076,0.001662468,0.0003345265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002462978,0.001476937,0.717779,0.0002335728,0.001242725,0.0003840241,0.000691761,0.2200566,0.0004990654,0.000720015,0.001945622,0.05250765],"study_design_scores_gemma":[0.0001243899,0.0006346449,0.07643289,0.00005749281,0.0003156549,0.0001441388,0.0002086789,0.9210364,0.0002734849,0.0004001425,0.0003434788,0.00002856913],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9886747,0.0005387799,0.00925964,0.0002199784,0.00003215676,0.0001444646,0.000284897,0.00005755036,0.0007878271],"genre_scores_gemma":[0.9953052,0.0001747401,0.003600968,0.00004010962,0.00001272631,0.0001113843,0.0005040275,0.00000745819,0.0002435206],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03360594,"threshold_uncertainty_score":0.06682062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02050052845179775,"score_gpt":0.299700178859337,"score_spread":0.2791996504075392,"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."}}