{"id":"W4389042358","doi":"10.30953/thmt.v8.452","title":"Near-Term Digital Health Predictions: A Glimpse into Tomorrow’s AI-driven Healthcare","year":2023,"lang":"en","type":"article","venue":"Telehealth and Medicine Today","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Health care; Realm; Workflow; Workforce; Digital transformation; Patient safety; Digital health; Computer science; Risk analysis (engineering); Data science; Business; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001222539,0.0003604696,0.0006696428,0.0004677865,0.001108555,0.0001303011,0.0006498041,0.0001542356,0.00003037071],"category_scores_gemma":[0.0005365295,0.000304251,0.00006146356,0.001680789,0.0002472665,0.0005698267,0.0003591053,0.0009207725,0.0001410459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002717107,"about_ca_system_score_gemma":0.001363861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003795707,"about_ca_topic_score_gemma":0.0005710448,"domain_scores_codex":[0.995845,0.0003092217,0.0009076576,0.0009329467,0.000772115,0.001233084],"domain_scores_gemma":[0.9965417,0.0003745055,0.0003188216,0.000951557,0.0001973729,0.001616],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00006408618,0.00009074989,0.1006505,0.003113621,0.0000304236,0.0001477045,0.03711141,0.0001705244,0.000007575516,0.02243278,0.08677044,0.7494102],"study_design_scores_gemma":[0.005378508,0.01042823,0.3797001,0.002806241,0.00002468504,0.0009051493,0.002569754,0.2373185,0.000004651369,0.0121234,0.3474157,0.001325125],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1265886,0.007471413,0.03148631,0.8247569,0.002948583,0.002084403,0.0000478663,0.003858288,0.0007576867],"genre_scores_gemma":[0.9668393,0.001580967,0.003536205,0.02613274,0.0009047762,0.0001349637,0.000159839,0.00005476871,0.0006564865],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8402507,"threshold_uncertainty_score":0.9999409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01973898556809438,"score_gpt":0.3364375658625249,"score_spread":0.3166985802944305,"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."}}