肺结核
舌头
医学
计算机科学
计算生物学
病毒学
生物
病理
出处
期刊:PubMed
[National Institutes of Health]
日期:2025-07-12
卷期号:48 (7): 605-608
被引量:1
标识
DOI:10.3760/cma.j.cn112147-20250214-00085
摘要
Tuberculosis (TB) remains a significant global public health threat. Achieving the 2035 target for TB elimination requires interrupting its community transmission, which depends critically on enhancing case detection. Active screening for TB in community populations is crucial in order to address the current shortfall in case detection through passive, symptom-based approaches. However, obtaining sputum specimens from these populations is challenging. In recent years, various alternative specimen types to sputum have emerged for use in active case-finding strategies for TB patients. Of these, the tongue swab is the most promising new, non-invasive specimen type for TB detection. Integrating advanced methods, such as artificial intelligence-based radiological imaging, could effectively facilitate the development of an active TB case-finding strategy in the community.
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