{"id":"W3043877665","doi":"10.5210/ojphi.v12i1.10611","title":"Improving Accuracy for Diabetes Mellitus Prediction by Using Deepnet","year":2020,"lang":"en","type":"article","venue":"Online Journal of Public Health Informatics","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"King Abdullah International Medical Research Center","keywords":"Machine learning; Decision tree; Artificial intelligence; Logistic regression; Computer science; Diabetes mellitus; Christian ministry; Data mining; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002148626,0.0007593061,0.0006272455,0.001460694,0.0003345518,0.001070881,0.0007718321,0.0007316832,0.001367914],"category_scores_gemma":[0.005292375,0.0002115095,0.0004948942,0.0008807221,0.0001510418,0.001121749,0.000764201,0.001019975,0.000589869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008879174,"about_ca_system_score_gemma":0.001297481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02325595,"about_ca_topic_score_gemma":0.02291501,"domain_scores_codex":[0.9994574,0.0001261126,0.0000625399,0.0001272912,0.0001197249,0.0001069302],"domain_scores_gemma":[0.9983253,0.0007844509,0.0001346758,0.0001389491,0.0005363354,0.00008023818],"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":[0.001119102,0.001000115,0.1318352,0.0002300652,0.0003555299,0.0003475458,0.0001488958,0.2536777,0.004455498,0.001393722,0.0142961,0.5911405],"study_design_scores_gemma":[0.00001770593,0.00008500402,0.006257857,0.00003407041,0.00003752884,0.00004822165,0.00005732702,0.9892507,0.002632209,0.0006674862,0.0008988577,0.0000130737],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8751139,0.003717995,0.1037083,0.001818369,0.0006521649,0.000118683,0.003113589,0.003811807,0.007945199],"genre_scores_gemma":[0.96434,0.0005720225,0.03021896,0.0001807644,0.00006893442,0.0000295239,0.002916991,0.00003018682,0.001642637],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02325595,"threshold_uncertainty_score":0.04624116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2982121040592978,"score_gpt":0.4843266758629524,"score_spread":0.1861145718036545,"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."}}