Research progress of artificial intelligence in pulmonary tuberculosis imaging diagnosis and drug resistance prediction

doi:10.19982/j.issn.1000-6621.20240123

Abstract

Abstract:

Tuberculosis (TB) is the leading cause of death from a single infectious disease worldwide. Early diagnosis of pulmonary tuberculosis (PTB) and identification of drug resistant tuberculosis are of great significance, but non-invasive and precise diagnosis and treatment are still limited. With the development of medical mega data, artificial intelligence (AI) has been gradually applied to PTB research. AI mining high flux characteristics from image, to provide the possibility of non-invasive and reproducible evaluation of lesions. In this paper, the research progress of AI technology in PTB image diagnosis and differential diagnosis, disease monitoring and drug resistance prediction in recent years is reviewed, with a view to promoting the clinical translation of AI diagnosis and drug resistance prediction technology for PTB, and providing support for the realization of precision medicine.

Key words: Tuberculosis, pulmonary, Tomography, X-ray computed, Artificial intelligence-assisted diagnosis, Models, statistical, Review literature as topic

CLC Number:

R81
R521

Li Wenhan, Yang Jing, Li Chunhua. Research progress of artificial intelligence in pulmonary tuberculosis imaging diagnosis and drug resistance prediction[J]. Chinese Journal of Antituberculosis, 2024, 46(9): 1098-1103. doi: 10.19982/j.issn.1000-6621.20240123

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