{"id":"W4289520941","doi":"10.1002/cpe.7219","title":"Machine learning and IoT‐based model for patient monitoring and early prediction of diabetes","year":2022,"lang":"en","type":"article","venue":"Concurrency and Computation Practice and Experience","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pan Am Clinic","funders":"","keywords":"Machine learning; Computer science; Naive Bayes classifier; Artificial intelligence; Random forest; Support vector machine; Decision tree; Receiver operating characteristic; Logistic regression; Python (programming language)","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":[0.000562053,0.000456562,0.0005889056,0.0005174204,0.0002931995,0.0006662034,0.0006719973,0.0006795287,0.00214096],"category_scores_gemma":[0.001325439,0.0001909113,0.0006266622,0.0003747686,0.0001989857,0.0003835775,0.0003451336,0.000664981,0.0004509774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006821033,"about_ca_system_score_gemma":0.0008250433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01291107,"about_ca_topic_score_gemma":0.005606843,"domain_scores_codex":[0.9997627,0.00005156535,0.00001636253,0.00006427817,0.00005637647,0.0000487447],"domain_scores_gemma":[0.9995918,0.0001904683,0.00004450614,0.00001721107,0.0001389542,0.00001714231],"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":[0.0001244868,0.0001340225,0.00885196,0.00004030283,0.00005157692,0.0001221502,0.00003286342,0.963674,0.0008411892,0.001468947,0.001136926,0.02352153],"study_design_scores_gemma":[0.000002474588,0.00001685655,0.0005985443,0.000003110454,0.000006079424,0.00001191408,0.000002484704,0.9988986,0.00009617248,0.0002383256,0.0001227956,0.000002630469],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3618287,0.001470341,0.6175343,0.00187631,0.0004122821,0.0001907502,0.001449357,0.002107195,0.01313092],"genre_scores_gemma":[0.9830605,0.0002629399,0.01242596,0.00007488399,0.00004049628,0.0001410607,0.0003696124,0.00001402552,0.003610343],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01291107,"threshold_uncertainty_score":0.02567184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1283474163911486,"score_gpt":0.4572647850993778,"score_spread":0.3289173687082292,"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."}}