{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.002762784,0.0004544192,0.003088256,0.0002173482,0.001481417,0.00001519556,0.0003231624,0.0002494455,0.000741225],"category_scores_gemma":[0.0015432,0.0003528301,0.0003668061,0.0003915717,0.00004262072,0.00004089521,0.000320248,0.001318487,0.0003506567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002606915,"about_ca_system_score_gemma":0.0001169157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007518815,"about_ca_topic_score_gemma":0.0001527612,"domain_scores_codex":[0.9931044,0.003299192,0.002002833,0.000583947,0.0003049168,0.0007047337],"domain_scores_gemma":[0.9930206,0.004899464,0.001372086,0.0004666325,0.00008714149,0.0001541068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[8.971392e-7,0.000005694907,0.00007981425,0.9178448,0.0001433576,0.000004765139,0.0001443047,2.462728e-7,8.815707e-10,0.0003384605,0.0002381653,0.08119945],"study_design_scores_gemma":[0.00001493408,0.00002473369,1.565851e-7,0.4317687,0.001493913,0.000001422071,0.000517708,0.00009199839,4.64267e-9,0.00003316955,0.5658792,0.0001740753],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000004042003,0.9821424,0.000001295167,0.0001996779,0.0006281611,0.01491814,0.0001141467,0.0001503494,0.00184171],"genre_scores_gemma":[0.000001735142,0.9853941,0.0001069742,0.0008547542,0.000129697,0.006589449,0.0002886844,0.000128424,0.00650625],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.565641,"threshold_uncertainty_score":0.9998924,"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."}}