人工智能在肺结核影像诊断及耐药性预测中的研究进展

doi:10.19982/j.issn.1000-6621.20240123

摘要/Abstract

摘要：

在全球范围内,结核病是单一传染病致死的主要原因,早期诊断肺结核和识别耐药结核病意义重大,但无创精准诊疗仍受限制。随着医疗大数据的发展,人工智能(artificial intelligence, AI)逐渐应用于肺结核研究。AI从影像中挖掘高通量特征,为无创、可重复评估病灶提供了可能。本文就近年来AI技术在肺结核影像诊断与鉴别诊断、病情监测及耐药性预测方面的研究进展进行综述,以期促进肺结核的AI诊断及耐药性预测技术的临床转化,为精准医疗的实现提供支持。

关键词: 结核,肺, 体层摄影术,X线计算机, 人工智能,诊断, 模型,统计学, 综述文献(主题)

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

中图分类号:

R81
R521

李汶翰, 杨静, 李春华. 人工智能在肺结核影像诊断及耐药性预测中的研究进展[J]. 中国防痨杂志, 2024, 46(9): 1098-1103. doi: 10.19982/j.issn.1000-6621.20240123

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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