A deep learning model using chest X-ray for identifying TB and NTM-LD patients: a cross-sectional study

CHIA-JUNG LIUTsai, Cheng CheCheng CheTsaiLU-CHENG KUOKuo, Po-ChihPo-ChihKuoMENG-RUI LEEJANN-YUAN WANGJEN-CHUNG KOJIN-YUAN SHIHHAO-CHIEN WANGCHONG-JEN YU2023-05-302023-05-302023-04-151869-4101https://scholars.lib.ntu.edu.tw/handle/123456789/631510Timely differentiating between pulmonary tuberculosis (TB) and nontuberculous mycobacterial lung disease (NTM-LD), which are radiographically similar, is important because infectiousness and treatment differ. This study aimed to evaluate whether artificial intelligence could distinguish between TB or NTM-LD patients by chest X-rays (CXRs) from suspects of mycobacterial lung disease.enArtificial intelligence; Chest radiography; Deep learning; Nontuberculous mycobacteria; Tuberculosis[SDGs]SDG3A deep learning model using chest X-ray for identifying TB and NTM-LD patients: a cross-sectional studyjournal article10.1186/s13244-023-01395-9370604192-s2.0-85153195868WOS:000969745700003https://api.elsevier.com/content/abstract/scopus_id/85153195868