{"id":"W4364357694","doi":"10.3389/fdgth.2023.1142822","title":"Interpretable clinical phenotypes among patients hospitalized with COVID-19 using cluster analysis","year":2023,"lang":"en","type":"article","venue":"Frontiers in Digital Health","topic":"COVID-19 Clinical Research Studies","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Centre intégré de santé et de services sociaux de Chaudière-Appalaches; Centre Intégré de Santé et de Services Sociaux des Laurentides; Centre Hospitalier de l’Université de Montréal","funders":"Fonds de Recherche du Québec - Santé; Fondation de l'Association des radiologistes du Québec; Réseau en Bio-Imagerie du Quebec","keywords":"Hierarchical clustering; Cluster analysis; Cluster (spacecraft); Medicine; Hypoxemia; Comorbidity; Data mining; Computer science; Internal medicine; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.003676316,0.0008333002,0.0007221118,0.002950002,0.0006315338,0.001683229,0.0008087034,0.0006130908,0.0007269872],"category_scores_gemma":[0.01327614,0.0002061041,0.001067259,0.001504423,0.0005845003,0.0005598657,0.001088957,0.0007747533,0.0001583368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002102158,"about_ca_system_score_gemma":0.001955069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02956517,"about_ca_topic_score_gemma":0.02302874,"domain_scores_codex":[0.998053,0.0007637868,0.0002093069,0.0004732136,0.0003166489,0.0001842178],"domain_scores_gemma":[0.9939563,0.002913821,0.001220925,0.0004346076,0.001183373,0.0002911062],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007368654,0.000102796,0.9573221,0.00007786373,0.0002808372,0.0001702586,0.0007202979,0.01771539,0.00122028,0.0004016723,0.001270192,0.0199814],"study_design_scores_gemma":[0.00008854445,0.0003411871,0.6180263,0.0001074579,0.0001929821,0.0004302268,0.002029204,0.3711306,0.001918277,0.004444493,0.001181393,0.0001093857],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9700754,0.0002065814,0.02690609,0.0004021958,0.00002424617,0.0002408022,0.001471664,0.0001379784,0.0005349141],"genre_scores_gemma":[0.9832792,0.00005070628,0.01488955,0.00003614364,0.0000103118,0.00008844722,0.001560754,0.00001432467,0.00007043784],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02956517,"threshold_uncertainty_score":0.05878615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04916975598996007,"score_gpt":0.4418513212569185,"score_spread":0.3926815652669584,"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."}}