{"id":"W4365143687","doi":"10.1038/s41586-023-05881-4","title":"Foundation models for generalist medical artificial intelligence","year":2023,"lang":"en","type":"review","venue":"Nature","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":1575,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto","funders":"National Center for Advancing Translational Sciences; Army Research Office; National Human Genome Research Institute; National Institute of Neurological Disorders and Stroke; Multidisciplinary University Research Initiative; Wu Tsai Neurosciences Institute, Stanford University; National Science Foundation; National Institutes of Health; Advanced Research Projects Agency; Defense Advanced Research Projects Agency","keywords":"Computer science; Set (abstract data type); Artificial intelligence; Modalities; Task (project management); Data science; Machine learning","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":[0.002252439,0.0007941528,0.0008205116,0.00173864,0.0002579031,0.002098934,0.001530953,0.001408516,0.005214557],"category_scores_gemma":[0.003499808,0.0003615888,0.0009159658,0.001585184,0.001744418,0.002762812,0.001173866,0.003191125,0.002602965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001856198,"about_ca_system_score_gemma":0.002250805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002191156,"about_ca_topic_score_gemma":0.00190861,"domain_scores_codex":[0.9993535,0.0002165516,0.00005959949,0.00009948156,0.0002406849,0.00003031864],"domain_scores_gemma":[0.9982218,0.001177464,0.00009231935,0.000201604,0.000259773,0.00004700539],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000291592,0.0000486794,0.000383566,0.004735527,0.0001282539,0.0001033457,0.00009362605,0.009651619,0.0005850434,0.622022,0.03341522,0.3288039],"study_design_scores_gemma":[0.0000197393,0.00004382564,0.0005106991,0.002827117,0.00005565595,0.0003039635,0.00004856445,0.01762513,0.0006819984,0.4815177,0.4963266,0.00003896748],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.002084686,0.6535757,0.2612644,0.0179525,0.001571893,0.0001754181,0.0007429669,0.0006675186,0.06196481],"genre_scores_gemma":[0.08180057,0.7684698,0.1266232,0.005383099,0.001995942,0.0006281832,0.001674716,0.0001843853,0.01324011],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005214557,"threshold_uncertainty_score":0.01744437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1777555539515253,"score_gpt":0.4640209167861247,"score_spread":0.2862653628345994,"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."}}