{"id":"W3124919495","doi":"10.2196/24973","title":"Deep Learning Models for Predicting Severe Progression in COVID-19-Infected Patients: Retrospective Study","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Science and ICT, South Korea; National Research Foundation of Korea; Ministry of Environment; National Research Foundation","keywords":"Medicine; Coronavirus disease 2019 (COVID-19); Convolutional neural network; Artificial intelligence; Retrospective cohort study; Pneumonia; Internal medicine; Computer science; Disease","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002015414,0.000582552,0.0004886467,0.001353978,0.0002506509,0.0007916556,0.0005485516,0.0005023116,0.001036185],"category_scores_gemma":[0.004667592,0.0003197814,0.0009070319,0.0007769727,0.0002361631,0.0007853628,0.0007252634,0.001010954,0.0003439244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005474595,"about_ca_system_score_gemma":0.0005425228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004971884,"about_ca_topic_score_gemma":0.004321769,"domain_scores_codex":[0.9993988,0.0001890025,0.00007523933,0.0001478918,0.00009641997,0.00009265643],"domain_scores_gemma":[0.9981078,0.000682032,0.0003765793,0.0002468291,0.0003868821,0.0001998475],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003741226,0.0001648108,0.9850772,0.00002527391,0.0002073486,0.0001589754,0.00003778731,0.003276097,0.0002327208,0.00007962378,0.0007082726,0.009657821],"study_design_scores_gemma":[0.00008697261,0.0009125023,0.7605671,0.0001111395,0.000598505,0.001238253,0.0006156607,0.2316239,0.001255571,0.0007003782,0.002232352,0.00005774258],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994603,0.0006112136,0.002786245,0.0001194162,0.00002021483,0.00003913952,0.001399907,0.00002323451,0.0003976844],"genre_scores_gemma":[0.996339,0.0002556038,0.001002345,0.00003092052,0.00001542916,0.00003171237,0.002157424,0.000007032801,0.0001606347],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004971884,"threshold_uncertainty_score":0.01065862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0296584031342313,"score_gpt":0.3642252336165216,"score_spread":0.3345668304822903,"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."}}