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
孙珊珊 1侯代伦 1李亮2
作者信息
- 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
- 折叠
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.
Abstract
The incidence of drug-resistant tuberculosis(DR-TB)continues to increase,posing a threat to global health secu-rity.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 re-view the literature on AI and DR-TB imaging and genetics,focusing on the superior performance of AI in identifying drug resis-tance 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Key words
Artificial Intelligence/Drug-resistant Tuberculosis/Radiology/Genetics引用本文复制引用
基金项目
北京市医院管理中心临床医学发展专项(XMLX202146)
北京市临床重点专科建设项目(20201214)
出版年
2024
NETL
NSTL
维普
万方数据