{"id":"W4205163905","doi":"10.1109/smc52423.2021.9659019","title":"Efficient Deep Neural Network for an Automated Detection of COVID-19 using CT images","year":2021,"lang":"en","type":"article","venue":"2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Convolutional neural network; Coronavirus disease 2019 (COVID-19); Radiography; Pneumonia; Artificial intelligence; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Radiology; Pandemic; Computed tomography; Population; Computer science; Medicine; Disease; Pathology; Internal medicine; Infectious disease (medical specialty)","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":[0.0004621976,0.000792921,0.0004378807,0.000768472,0.0002687809,0.0004820907,0.000739722,0.0007873884,0.001479381],"category_scores_gemma":[0.0009795448,0.0002858151,0.0005505804,0.0004278292,0.0001930069,0.000499298,0.0004887205,0.0007539328,0.0005673676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000742505,"about_ca_system_score_gemma":0.0007897539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01343634,"about_ca_topic_score_gemma":0.01168609,"domain_scores_codex":[0.9998199,0.00002482315,0.00001282345,0.0000533519,0.00004468077,0.00004430082],"domain_scores_gemma":[0.9997783,0.00007715305,0.00002668167,0.00001789115,0.00008423803,0.00001564616],"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":[0.0006721664,0.0003738717,0.009784609,0.0001594419,0.0001630482,0.0004343741,0.00007368352,0.3328992,0.03825155,0.001668103,0.007160611,0.6083593],"study_design_scores_gemma":[0.000004218676,0.00003108378,0.0008111667,0.000006189041,0.00001134749,0.00003742157,0.00000577763,0.9952932,0.003208557,0.0002998879,0.0002863462,0.000004717579],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2758872,0.002547392,0.7084541,0.0009572368,0.0002635707,0.0001764836,0.0008908781,0.005556542,0.005266556],"genre_scores_gemma":[0.8972217,0.0006968284,0.09480951,0.0002538911,0.00006356776,0.0001069438,0.001219897,0.00006712283,0.005560532],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01343634,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08831818685297786,"score_gpt":0.3773266215262757,"score_spread":0.2890084346732978,"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."}}