{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000850219,0.0001583961,0.0004032904,0.0004210182,0.0006696756,0.00001092983,0.0001507583,0.0002259225,0.00004242278],"category_scores_gemma":[0.0003878003,0.0001500731,0.0001730949,0.0009143892,0.0005079672,0.0001049889,0.00001361939,0.001063615,8.190753e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005464164,"about_ca_system_score_gemma":0.0005024836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002146519,"about_ca_topic_score_gemma":0.0001012502,"domain_scores_codex":[0.9985313,0.0001580545,0.0004641131,0.000353117,0.0002373285,0.0002561225],"domain_scores_gemma":[0.9979053,0.001497617,0.0002362018,0.0002051539,0.00006991163,0.00008577186],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009462131,0.002172548,0.7407642,0.002134259,0.0003601925,0.00001894238,0.02074861,0.1925424,0.00159378,0.0002444005,0.0004513964,0.03802305],"study_design_scores_gemma":[0.03128462,0.001702675,0.04601889,0.0009903001,0.0006182119,0.00007445685,0.04351616,0.8671087,0.004217927,0.001577453,0.002246307,0.000644288],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8974808,0.0002439242,0.08645353,0.01452087,0.0001057707,0.001046654,0.00002327283,0.0001203926,0.000004717369],"genre_scores_gemma":[0.993737,0.00008404684,0.001017658,0.00474282,0.000007326585,0.0003627912,0.00001313985,0.00002156318,0.00001361881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6947453,"threshold_uncertainty_score":0.6119803,"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."}}