{"id":"W4288783441","doi":"10.1109/tts.2022.3195114","title":"Assessing Trustworthy AI in Times of COVID-19: Deep Learning for Predicting a Multiregional Score Conveying the Degree of Lung Compromise in COVID-19 Patients","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Technology and Society","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cégep André Laurendeau","funders":"Innovation and Networks Executive Agency; Berlin Institute of Health; Humanitas University; Universitätsspital Zürich; Universität Bremen; Università di Pisa; Università degli Studi di Brescia; Scuola Superiore Sant'Anna; Karolinska Institutet; Sunway University; University of Technology Sydney; University of New England; Humanitas Research Hospital; Seoul National University; NYU Grossman School of Medicine; Technische Universiteit Delft; Birmingham City University; European Commission; Justice Programme; Università di Bologna; Faculty of Engineering and Information Technology, University of Technology Sydney; University of Manchester; Connecting Europe Facility; York University; Wellcome Trust; Université du Québec à Montréal; Stony Brook University; University of Cambridge; Háskóli Íslands; Swinburne University of Technology; Ohio State University; Scuola Normale Superiore; Horizon 2020 Framework Programme; Turun Yliopisto; Erasmus Universitair Medisch Centrum Rotterdam; European University Institute; University of Oxford; Technische Universiteit Eindhoven; Harvard University; Hackensack Meridian Health","keywords":"Coronavirus disease 2019 (COVID-19); Trustworthiness; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Degree (music); Compromise; Medicine; Computer science; Artificial intelligence; Internal medicine; Virology; Physics; Outbreak; Political science; Computer security","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":[0.003128334,0.0006917907,0.0003821076,0.001294617,0.0003342149,0.001090676,0.0004762805,0.0009257809,0.0006412728],"category_scores_gemma":[0.01248173,0.0001295941,0.0004078761,0.0005343395,0.0004066181,0.0007234684,0.001075327,0.001246282,0.0002774495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008090201,"about_ca_system_score_gemma":0.0007638045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003713882,"about_ca_topic_score_gemma":0.004636238,"domain_scores_codex":[0.9984248,0.0008033044,0.0001437954,0.0002530426,0.0002070219,0.0001681061],"domain_scores_gemma":[0.9930315,0.004556171,0.0007987435,0.0003789106,0.0007866713,0.0004480594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001645147,0.001002373,0.4701647,0.0003386373,0.0004154369,0.0006186197,0.002035026,0.1835538,0.00775231,0.001466123,0.007735692,0.3232723],"study_design_scores_gemma":[0.00004084486,0.0005910844,0.05668542,0.00009672226,0.00007684567,0.0001883751,0.0009024254,0.9328892,0.004397577,0.002751914,0.001338506,0.00004105567],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9318511,0.0004831003,0.0623359,0.001280538,0.00008790153,0.0002051219,0.0005146973,0.0004689541,0.002772576],"genre_scores_gemma":[0.9866165,0.00007614505,0.01246959,0.0001014476,0.00001967869,0.0000458346,0.0003621312,0.000009513707,0.000299174],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003713882,"threshold_uncertainty_score":0.0165444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04672944734666615,"score_gpt":0.3356357295238923,"score_spread":0.2889062821772261,"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."}}