{"id":"W4403758117","doi":"10.3122/jabfm.2023.230381r1","title":"Using Primary Health Care Electronic Medical Records to Predict Hospitalizations, Emergency Department Visits, and Mortality: A Systematic Review","year":2024,"lang":"en","type":"review","venue":"The Journal of the American Board of Family Medicine","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Michael's Hospital","funders":"University of Toronto; Canadian Institutes of Health Research; Government of Ontario","keywords":"Emergency department; Medicine; Health records; Primary care; Emergency medicine; Medical emergency; Medical record; Electronic health record; Health care; Family medicine; Nursing; Internal medicine","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":[0.01368023,0.0016032,0.008558775,0.01249197,0.0006016656,0.003029861,0.002342798,0.002136396,0.003855437],"category_scores_gemma":[0.07474247,0.001244262,0.00885004,0.01577081,0.001028738,0.003013057,0.001407509,0.001298968,0.0004161546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00372528,"about_ca_system_score_gemma":0.01361921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01197825,"about_ca_topic_score_gemma":0.02633736,"domain_scores_codex":[0.9850988,0.005466991,0.00490982,0.001134499,0.003046488,0.000343336],"domain_scores_gemma":[0.9235371,0.05991608,0.0109126,0.0008085842,0.004430123,0.0003955116],"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":[0.0001151306,0.00001928542,0.00255505,0.9592237,0.01042931,0.00007144241,0.0001677134,0.00009532012,0.00004015303,0.0001194609,0.001142966,0.02602048],"study_design_scores_gemma":[0.0001732412,0.0001809107,0.008289685,0.9203694,0.06308482,0.0002851618,0.0002548347,0.000151108,0.00009863936,0.0001833063,0.006894141,0.00003472005],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001587393,0.9966157,0.0001733179,0.0003000797,0.00008455787,0.0003716684,0.0006382936,0.00001110405,0.0002179228],"genre_scores_gemma":[0.02434017,0.9726374,0.0008950246,0.0005901276,0.0001038645,0.0008867447,0.0004487356,0.000006110357,0.00009194878],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01368023,"threshold_uncertainty_score":0.07234883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04812500724831532,"score_gpt":0.4161107367128867,"score_spread":0.3679857294645714,"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."}}