{"id":"W4280516831","doi":"10.2196/37365","title":"Combating COVID-19 Using Generative Adversarial Networks and Artificial Intelligence for Medical Images: Scoping Review","year":2022,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Generative grammar; Adversarial system; Artificial intelligence; Computer science; Scarcity; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Computed tomography; Machine learning; Radiology; Medicine; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008936037,0.001586102,0.003884074,0.006368442,0.0005495895,0.003009722,0.002194396,0.002994651,0.006184875],"category_scores_gemma":[0.04908137,0.0008447852,0.00691127,0.004256658,0.001035289,0.002529424,0.001595484,0.00197012,0.0008678099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001912585,"about_ca_system_score_gemma":0.008049177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005074015,"about_ca_topic_score_gemma":0.006946377,"domain_scores_codex":[0.996314,0.001461694,0.0009878163,0.000386535,0.0007400414,0.0001098913],"domain_scores_gemma":[0.9588147,0.03591307,0.002198382,0.000599609,0.002313241,0.0001608828],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0002151363,0.00006205121,0.00064261,0.5414786,0.003927074,0.0001366463,0.0001934583,0.001810731,0.0003021087,0.004119025,0.008951453,0.4381611],"study_design_scores_gemma":[0.0001243662,0.000475706,0.002418867,0.7853864,0.01860567,0.0008575096,0.0003693948,0.001875384,0.0007883245,0.008038023,0.1809559,0.0001044894],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001846442,0.9974745,0.000878279,0.0005788109,0.000142207,0.0001003627,0.0001064449,0.00001363287,0.0005211458],"genre_scores_gemma":[0.003291128,0.9938692,0.001574749,0.0005351966,0.0001590673,0.000263779,0.0001285983,0.00001062035,0.0001676838],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.008936037,"threshold_uncertainty_score":0.04725879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09526057330090464,"score_gpt":0.4365261673392923,"score_spread":0.3412655940383877,"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."}}