人工智能在登革热管理中的应用:对未来方向的展望。

IF 1.5 4区 医学 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Mohammed Hussein, Elshimaa Ali, Yassin Kamal, Ali Elhouni, E L Mardi Ems, Yousif Eltayeb, Ali Awadallah Saeed, Ahmed Hassan Fahal
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引用次数: 0

摘要

登革热仍然是一项重大的公共卫生挑战,特别是在热带和亚热带地区。由于每年有数百万人受到影响,而且由于城市化和气候变化,该病的流行率不断上升,因此有效的管理战略至关重要。将人工智能(AI)纳入医疗保健为登革热的管理提供了变革性的可能性。人工智能驱动的系统可以通过分析大量流行病学、环境和社会行为数据来确定早期预警指标并预测疫情趋势,从而改善疾病监测。由人工智能算法驱动的增强型诊断仪器可以加快和改进病例识别,特别是在资源受限的环境中。此外,人工智能可以通过精确定位高风险地区和优化预防措施的实施来加强有针对性的病媒控制策略。人工智能可以优化医疗机构的资源配置。这些应用有可能大大减轻登革热的负担,改善患者的预后,并加强卫生系统的复原力。随着人工智能技术的进步,预计其在公共卫生领域的影响将日益扩大,从而促进符合联合国可持续发展目标(sdg)的创新、数据驱动战略,以加强全球卫生公平和疾病预防。持续的研究、合作和社区参与对于充分发挥人工智能在应对这一紧迫的公共卫生挑战方面的潜力至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The utility of artificial intelligence in the management of dengue fever: a perspective on future directions.

Dengue fever remains a significant public health challenge, particularly in tropical and subtropical regions. With millions affected each year and the increasing prevalence of the disease due to urbanisation and climate change, effective management strategies are crucial. The incorporation of artificial intelligence (AI) in healthcare presents transformative possibilities for the management of dengue fever. AI-driven systems can improve disease surveillance by analyzing extensive volumes of epidemiological, environmental, and socio-behavioral data to identify early warning indicators and forecast outbreak trends. Enhanced diagnostic instruments driven by AI algorithms can expedite and refine case identification, especially in resource-constrained environments. Moreover, AI can enhance targeted vector control tactics by pinpointing high-risk areas and optimizing the implementation of preventive measures. AI can optimize resource allocation in healthcare institutions. These applications have the potential to substantially alleviate the burden of dengue fever, enhance patient outcomes, and fortify health system resilience. As AI technologies progress, their influence in public health is expected to grow, facilitating creative, data-driven strategies that correspond with the United Nations Sustainable Development Goals (SDGs) to enhance global health equity and disease prevention. Continued research, collaboration, and community engagement will be crucial to realising the full potential of AI in addressing this pressing public health challenge.

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来源期刊
Transactions of The Royal Society of Tropical Medicine and Hygiene
Transactions of The Royal Society of Tropical Medicine and Hygiene 医学-公共卫生、环境卫生与职业卫生
CiteScore
4.00
自引率
9.10%
发文量
115
审稿时长
4-8 weeks
期刊介绍: Transactions of the Royal Society of Tropical Medicine and Hygiene publishes authoritative and impactful original, peer-reviewed articles and reviews on all aspects of tropical medicine.
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