Application of artificial intelligence in digital chest radiography reading for pulmonary tuberculosis screening
10.1016/j.cdtm.2021.02.001
- VernacularTitle:Application of artificial intelligence in digital chest radiography reading for pulmonary tuberculosis screening
- Author:
Xue-Fang CAO
1
;
Yuan LI
;
He-Nan XIN
;
Hao-Ran ZHANG
;
Madhukar PAI
;
Lei GAO
Author Information
1. NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, And Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
- Publication Type:Journal Article
- Keywords:
Tuberculosis;
Artificial intelligence;
Digital chest radiography;
Diagnosis;
Triage
- From:
Chronic Diseases and Translational Medicine
2021;07(1):35-40
- CountryChina
- Language:English
-
Abstract:
Currently, the diagnosis of tuberculosis (TB) is mainly based on the comprehensive consideration of the patient's symptoms and signs, laboratory examinations and chest radiography (CXR). CXR plays a pivotal role to support the early diagnosis of TB, especially when used for TB screening and differential diagnosis. However, high cost of CXR hardware and shortage of certified radiologists poses a major challenge for CXR application in TB screening in resource limited settings. The latest development of artificial intelligence (AI) combined with the accumulation of a large number of medical images provides new opportunities for the establishment of computer-aided detection (CAD) systems in the medical applications, especially in the era of deep learning (DL) technology. Several CAD solutions are now commercially available and there is growing evidence demonstrate their value in imaging diagnosis. Recently, WHO published a rapid communication which stated that CAD may be used as an alternative to human reader interpretation of plain digital CXRs for screening and triage of TB.
