{"id":"W4200387391","doi":"10.1109/embc46164.2021.9629689","title":"Automated Detection of COVID-19 Cases using Recent Deep Convolutional Neural Networks and CT images","year":2021,"lang":"en","type":"article","venue":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine &amp; Biology Society (EMBC)","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"","keywords":"Convolutional neural network; Coronavirus disease 2019 (COVID-19); Computer science; Deep learning; Artificial intelligence; Pneumonia; Medical imaging; Feature extraction; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Pattern recognition (psychology); Computer vision; Disease; Machine learning; Medicine; Pathology; Infectious disease (medical specialty)","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":[0.0006109352,0.001026513,0.0003790623,0.002333335,0.0002047949,0.0006922926,0.0006959484,0.0008441387,0.0006320538],"category_scores_gemma":[0.001898332,0.0002965853,0.0005996633,0.0006669632,0.0002529494,0.0004867293,0.0006080786,0.0005431168,0.0003341155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007030141,"about_ca_system_score_gemma":0.0004251885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00810344,"about_ca_topic_score_gemma":0.011336,"domain_scores_codex":[0.9996282,0.00006872459,0.00003370086,0.0001119298,0.00008457309,0.00007276104],"domain_scores_gemma":[0.999534,0.0001375807,0.00009589989,0.00004780491,0.0001358291,0.00004883386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001395141,0.0005996772,0.08340789,0.0003295921,0.000386018,0.002565564,0.0001632792,0.166373,0.06486177,0.001336803,0.009359681,0.6692216],"study_design_scores_gemma":[0.00001452408,0.00007526629,0.01113686,0.00002720373,0.00004011034,0.0004737256,0.00003498492,0.972999,0.0137566,0.0006690928,0.0007582979,0.00001414857],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6932599,0.002551477,0.2947382,0.0008841073,0.0002110367,0.0002992433,0.00175342,0.003058231,0.003244295],"genre_scores_gemma":[0.913788,0.000809235,0.08129735,0.0002052187,0.00008934051,0.00006941912,0.002433703,0.00004338043,0.001264508],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00810344,"threshold_uncertainty_score":0.01611251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06346654307028936,"score_gpt":0.3590250045200895,"score_spread":0.2955584614498001,"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."}}