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。鉴于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。
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.
作者
施亮
张键锋
李伟
杨坤
SHI Liang;ZHANG Jian-feng;LI Wei;YANG Kun(Jiangsu Institute of Parasitic Diseases,National Health Commission Key Laboratory of Parasitic Disease Control and Prevention,Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology,Wuxi,Jiangsu 214064,China;Public Health Research Center,Jiangnan University,Wuxi,Jiangsu 214064,China;School of Public Health,Nanjing Medical University,Nanjing,Jiangsu 211166,China)
出处
《中国血吸虫病防治杂志》
CAS
CSCD
北大核心
2022年第5期445-452,共8页
Chinese Journal of Schistosomiasis Control
基金
江苏省国际科技合作项目(BZ2020003)
江苏省卫生健康委医学科研项目(M2021102)
江苏省无锡市科技发展资金(Y20212048)
江苏省无锡市卫生健康委科研项目(M202121)
江苏省血地寄科研课题(X202105)
江南大学公共卫生研究中心课题(JUPH201837,JUPH202008)。
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
Tropical infectious disease
Artificial intelligence
Machine learning
Deep learning
Public health
Global health