人工智能在预测耐药性肺结核中的应用进展  

Application progress of artificial intelligence in predicting drug-resistant tuberculosis

作　　者：孙珊珊 侯代伦 李亮[2] SUN Shanshan;HOU Dailun;LI Liang(Department of Radiology,Beijing Tuberculosis and Thoracic Tumor Research Institute,Beijing 101149,China;Clinical Center on Tuberculosis Control,Beijing Chest Hospital,Capital Medical University,Beijing Tuberculosis&Thoracic Tumor Research Institute,Beijing 101149,China)

机构地区：[1]北京市结核病胸部肿瘤研究所医学影像科,北京101149 [2]北京市结核病胸部肿瘤研究所院办公室,北京101149

出　　处：《医学影像学杂志》2024年第4期129-131,共3页Journal of Medical Imaging

基　　金：北京市医院管理中心临床医学发展专项经费资助(编号:XMLX202146);北京市临床重点专科项目(编号:20201214)。

摘　　要：耐药性肺结核(DR-TB)发病率持续上升,对全球卫生安全造成威胁。而随着科技日益进步,人工智能(AI)越来越广泛地应用于医学领域,对DR-TB来说,有效地节省了人力和时间成本,并提高了检测效率和精确度。本文回顾了AI与DR-TB放射学和基因学的文献资料,重点介绍了AI在识别肺结核的耐药性方面表现出的优越性能,这有助于临床医师及时做出临床决策,为患者制定治疗计划,为肺结核管理提供参考。The incidence of drug-resistant tuberculosis(DR-TB)continues to increase,posing a threat to global health security.With the advancement of science and technology,artificial intelligence(AI)is more and more widely used in the medical field.For DR-TB,it effectively saves labor and time costs,and improves detection efficiency and accuracy.In this article,we review the literature on AI and DR-TB imaging and genetics,focusing on the superior performance of AI in identifying drug resistance in pulmonary tuberculosis,which helps clinicians make timely clinical decisions,develop treatment plans for patients and provide reference for tuberculosis management.

关 键 词：人工智能 耐药性肺结核 放射学 基因学 

分 类 号：R521[医药卫生—内科学] R445[医药卫生—临床医学]