{"id":"W3134296997","doi":"10.1016/j.cdtm.2021.02.001","title":"Application of artificial intelligence in digital chest radiography reading for pulmonary tuberculosis screening","year":2021,"lang":"en","type":"review","venue":"Chronic Diseases and Translational Medicine","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University Health Centre","funders":"National Major Science and Technology Projects of China","keywords":"Medicine; Triage; Pulmonary tuberculosis; Tuberculosis; Medical physics; CAD; Economic shortage; Differential diagnosis; Radiology; Medical emergency; 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":[0.0008576346,0.0006063854,0.001054195,0.002992295,0.0002135755,0.001048759,0.0006991066,0.001091316,0.003262205],"category_scores_gemma":[0.001789752,0.0002625573,0.0008918691,0.002276947,0.0004120136,0.00113512,0.0006346448,0.001655413,0.001347521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000563508,"about_ca_system_score_gemma":0.0008498038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001327045,"about_ca_topic_score_gemma":0.001941496,"domain_scores_codex":[0.9995832,0.000115507,0.00007480321,0.00005840099,0.0001446291,0.00002347193],"domain_scores_gemma":[0.999186,0.0005451648,0.00006392386,0.0000172945,0.0001637252,0.00002384995],"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":[0.00004709402,0.00006514544,0.0002904181,0.02858353,0.000189432,0.0002002709,0.00008299428,0.0003786741,0.000652154,0.003811267,0.01715267,0.9485462],"study_design_scores_gemma":[0.0000339733,0.0001912569,0.002854716,0.01864036,0.0004272016,0.002131518,0.0001083093,0.0004952573,0.0009551325,0.004300702,0.9698033,0.00005819093],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001405165,0.9978015,0.0002079277,0.0003014559,0.0001596332,0.000008682314,0.00001621974,0.000007136838,0.001356962],"genre_scores_gemma":[0.00155034,0.9970999,0.0005329712,0.0002779045,0.0001439303,0.00001105135,0.00003008634,0.000002064211,0.0003518588],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003262205,"threshold_uncertainty_score":0.01091313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05439379515475865,"score_gpt":0.3667434104867109,"score_spread":0.3123496153319523,"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."}}