{"id":"W3126902822","doi":"10.1109/icoiact50329.2020.9332153","title":"Detection of COVID-19 on Chest X-Ray Images using Inverted Residuals Structure-Based Convolutional Neural Networks","year":2020,"lang":"en","type":"article","venue":"","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Pooling; Coronavirus disease 2019 (COVID-19); Dropout (neural networks); Convolutional neural network; Computer science; Artificial intelligence; F1 score; Pattern recognition (psychology); Artificial neural network; Medicine; Disease; Internal medicine; Machine learning","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":[0.0003455171,0.000839306,0.0003880504,0.001191043,0.0001814911,0.0004218273,0.0006503081,0.0005324158,0.0007961004],"category_scores_gemma":[0.0008642998,0.000227682,0.0005596077,0.0003948381,0.0001874881,0.0004004572,0.0005222199,0.0004560031,0.0003909179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004636218,"about_ca_system_score_gemma":0.0004736003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009515449,"about_ca_topic_score_gemma":0.01378632,"domain_scores_codex":[0.9997944,0.0000219909,0.00001507152,0.00006400087,0.0000555384,0.00004905488],"domain_scores_gemma":[0.999804,0.0000457486,0.00003708589,0.00002106207,0.00007246993,0.00001970394],"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":[0.001044557,0.0004562626,0.04238414,0.0002387019,0.0003099926,0.00129486,0.0001494428,0.07844792,0.1186727,0.001073908,0.006642232,0.7492853],"study_design_scores_gemma":[0.00001540565,0.0001552801,0.01353457,0.00002402573,0.00006667409,0.0003960063,0.00003888461,0.9615163,0.02266002,0.0004627408,0.001112306,0.00001775293],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6030709,0.002174667,0.3834246,0.00053225,0.0002040374,0.0002453261,0.00132437,0.004677178,0.004346576],"genre_scores_gemma":[0.9013155,0.0006547644,0.09271695,0.000168058,0.00006828647,0.00004961772,0.001902641,0.00005650279,0.003067634],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009515449,"threshold_uncertainty_score":0.01892018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05466849146633976,"score_gpt":0.3204900955285503,"score_spread":0.2658216040622106,"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."}}