A deep learning model using chest X-ray for identifying TB and NTM-LD patients: a cross-sectional study
Journal
Insights into imaging
Journal Volume
14
Journal Issue
1
Date Issued
2023-04-15
Author(s)
Tsai, Cheng Che
Kuo, Po-Chih
Abstract
Timely 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.
Subjects
Artificial intelligence; Chest radiography; Deep learning; Nontuberculous mycobacteria; Tuberculosis
SDGs
Publisher
SPRINGER
Type
journal article