{"id":"W4214595570","doi":"10.3390/s22051843","title":"Machine Learning and Smart Devices for Diabetes Management: Systematic Review","year":2022,"lang":"en","type":"review","venue":"Sensors","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":141,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cegep de Sept Iles; Université du Québec à Chicoutimi; Université du Québec à Rimouski","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Diabetes mellitus; Scopus; Diabetes management; Wearable technology; Wearable computer; Medicine; Blood sugar; Computer science; Intensive care medicine; Artificial intelligence; MEDLINE; Risk analysis (engineering); Type 2 diabetes; Embedded system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00505632,0.001051292,0.005314012,0.005801592,0.0004385898,0.001796311,0.001591627,0.00182027,0.00649879],"category_scores_gemma":[0.02587656,0.0005751292,0.004879727,0.007690038,0.0005594368,0.001869378,0.0009635349,0.001080333,0.0003977675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002657999,"about_ca_system_score_gemma":0.007877045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006446538,"about_ca_topic_score_gemma":0.01709973,"domain_scores_codex":[0.996228,0.001358606,0.001200066,0.0002563792,0.0008094514,0.0001474977],"domain_scores_gemma":[0.9781709,0.01741664,0.002870055,0.0001875354,0.001173034,0.0001818371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0001357293,0.00002397657,0.0006493837,0.9451823,0.00427777,0.00007163059,0.00009202191,0.0001293574,0.00005108385,0.0002274065,0.002692926,0.04646639],"study_design_scores_gemma":[0.0002016321,0.0001557719,0.003481996,0.9463594,0.02834488,0.0003064079,0.0001369441,0.0001673446,0.00008965163,0.000321531,0.02040774,0.00002679296],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003847705,0.9988249,0.0000757778,0.0001975377,0.00006209862,0.0001124427,0.0001511782,0.000004131695,0.0001871075],"genre_scores_gemma":[0.006915664,0.9917454,0.0003689663,0.0003786092,0.00007115207,0.0002819217,0.0001339121,0.000002407587,0.0001018967],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.00649879,"threshold_uncertainty_score":0.02674073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2059935020980422,"score_gpt":0.4991403695490511,"score_spread":0.2931468674510089,"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."}}