Abstract: Since the global pandemic of coronavirus disease 2019 (COVID⁃19) in late 2019, artificial intelligence technology has shown increasing values in the research and control of tropical infectious diseases. The introduction of artificial intelligence technology has shown remarkable effectiveness to reduce the diagnosis and treatment burdens, reduce missing diagnosis and misdiagnosis, improve the surveillance and forecast ability and enhance the medicine and vaccine development efficiency. This paper summarizes the current applications of artificial intelligence in tropical infectious disease control and research and discusses the important values of artificial intelligence in disease diagnosis and treatment, disease surveillance and forecast, vaccine and drug discovery, medical and public health services and global health governance. However, artificial intelligence technology suffers from problems of single and inaccurate diagnosis, poor disease surveillance and forecast ability in open environments, limited capability of intelligent system services, big data management and model interpretability. Hereby, we propose suggestions with aims to improve multimodal intelligent diagnosis of multiple tropical infectious diseases, emphasize intelligent surveillance and forecast of vectors and high⁃risk populations in open environments, accelerate the research and development of intelligent management system, strengthen ethical security, big data management and model interpretability.

Key words: Tropical infectious disease, Artificial intelligence, Machine learning, Deep learning, Public health, Global health

摘要： 自新型冠状病毒肺炎疫情发生以来，人工智能技术在热带传染病领域应用的先进性逐渐凸显。人工智能技术的应用对缓解疾病诊疗负担、降低疾病漏诊和误诊率、提升疾病监测预警能力、提高医药和疫苗研发效率等均具有显著成效。本文分析了人工智能在热带传染病防控研究中的应用现状，论述了人工智能在该领域疾病诊疗、监测预警、疫苗与药物挖掘、医疗与公共卫生服务和全球卫生治理中的重要价值。根据人工智能助力热带传染病防控面临着诊断单一和不准确、开放环境监测预警能力不佳、智能系统服务能力有限、大数据管理困难、模型可解释性较差等方面的难题，本文提出了加强多种热带传染病多模态智能诊断、重视开放环境下媒介生物和风险人群智能监测预警、加快智能防控系统研发、强化伦理安全、大数据管理与模型可解释性等发展建议。

关键词: 热带传染病, 人工智能, 机器学习, 深度学习, 公共卫生, 全球卫生