{"id":"W3189257822","doi":"10.1016/j.compbiomed.2021.104665","title":"Artificial intelligence-driven assessment of radiological images for COVID-19","year":2021,"lang":"en","type":"review","venue":"Computers in Biology and Medicine","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":88,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; BC Cancer Agency","funders":"","keywords":"Artificial intelligence; Computer science; Radiomics; Identification (biology); Machine learning; Coronavirus disease 2019 (COVID-19); Deep learning; Convolutional neural network; Workflow; Medical imaging; Medicine; Disease; Pathology","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":[0.00150565,0.0009162866,0.001393656,0.003678492,0.0002052696,0.001423975,0.001434314,0.001396676,0.002929511],"category_scores_gemma":[0.005460582,0.000334314,0.001200821,0.001879727,0.0004959411,0.0009582667,0.0006868005,0.001258058,0.001438615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008400248,"about_ca_system_score_gemma":0.001566363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003206959,"about_ca_topic_score_gemma":0.004545358,"domain_scores_codex":[0.9994298,0.0001292104,0.00007536582,0.0000921583,0.0002484731,0.00002483785],"domain_scores_gemma":[0.9976923,0.001460269,0.0002080543,0.0000492013,0.0005389416,0.00005132095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.00007108966,0.00005653473,0.0009256516,0.0116994,0.0002108053,0.0001613661,0.00004073426,0.001386401,0.0009619234,0.002161913,0.0110391,0.971285],"study_design_scores_gemma":[0.0001618941,0.0006098436,0.01952741,0.04950614,0.002829057,0.009225662,0.0003686916,0.02559236,0.01138845,0.02779142,0.8526268,0.0003724088],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0008625537,0.9876019,0.007463787,0.00074744,0.0002327056,0.00006795414,0.0001663339,0.0001038822,0.002753475],"genre_scores_gemma":[0.02025161,0.9598503,0.01638951,0.0007676323,0.0004424917,0.00009290401,0.0006376756,0.00002754692,0.001540332],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003678492,"threshold_uncertainty_score":0.009800196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2184261199307491,"score_gpt":0.5294856422280917,"score_spread":0.3110595222973426,"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."}}