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Inform. med."],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Prompt and correct detection of pulmonary tuberculosis (PTB) is critical in preventing its spread. We aimed to develop a deep learning\u2013based algorithm for detecting PTB on chest X-ray (CXRs) in the emergency department. This retrospective study included 3498 CXRs acquired from the National Taiwan University Hospital (NTUH). The images were chronologically split into a training dataset, NTUH-1519 (images acquired during the years 2015 to 2019; <jats:italic>n<\/jats:italic>\u2009=\u20092144), and a testing dataset, NTUH-20 (images acquired during the year 2020; <jats:italic>n<\/jats:italic>\u2009=\u20091354). Public databases, including the NIH ChestX-ray14 dataset (model training; 112,120 images), Montgomery County (model testing; 138 images), and Shenzhen (model testing; 662 images), were also used in model development. EfficientNetV2 was the basic architecture of the algorithm. Images from ChestX-ray14 were employed for pseudo-labelling to perform semi-supervised learning. The algorithm demonstrated excellent performance in detecting PTB (area under the receiver operating characteristic curve [AUC] 0.878, 95% confidence interval [CI] 0.854\u20130.900) in NTUH-20. The algorithm showed significantly better performance in posterior-anterior (PA) CXR (AUC 0.940, 95% CI 0.912\u20130.965, <jats:italic>p-value<\/jats:italic>\u2009&lt;\u20090.001) compared with anterior\u2013posterior (AUC 0.782, 95% CI 0.644\u20130.897) or portable anterior\u2013posterior (AUC 0.869, 95% CI 0.814\u20130.918) CXR. The algorithm accurately detected cases of bacteriologically confirmed PTB (AUC 0.854, 95% CI 0.823\u20130.883). Finally, the algorithm tested favourably in Montgomery County (AUC 0.838, 95% CI 0.765\u20130.904) and Shenzhen (AUC 0.806, 95% CI 0.771\u20130.839). A deep learning\u2013based algorithm could detect PTB on CXR with excellent performance, which may help shorten the interval between detection and airborne isolation for patients with PTB.<\/jats:p>","DOI":"10.1007\/s10278-023-00952-4","type":"journal-article","created":{"date-parts":[[2024,1,10]],"date-time":"2024-01-10T22:02:13Z","timestamp":1704924133000},"page":"589-600","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Deep Learning\u2013based Diagnosis of Pulmonary Tuberculosis on Chest X-ray in the Emergency Department: A Retrospective Study"],"prefix":"10.1007","volume":"37","author":[{"given":"Chih-Hung","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weishan","family":"Chang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meng-Rui","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joyce","family":"Tay","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cheng-Yi","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meng-Che","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Holger R.","family":"Roth","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dong","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Can","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weichung","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2981-4537","authenticated-orcid":false,"given":"Chien-Hua","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,1,10]]},"reference":[{"key":"952_CR1","unstructured":"Global tuberculosis report 2021, Geneva: World Health Organization, 2021"},{"key":"952_CR2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0248493","volume":"16","author":"C Heffernan","year":"2021","unstructured":"Heffernan C, et al.: Individual and public health consequences associated with a missed diagnosis of pulmonary tuberculosis in the emergency department: A retrospective cohort study. 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