人工智能如何帮助我们进行急性呼吸道感染的流行病学研究和诊断?

IF 3.3 3区 医学 Q2 MICROBIOLOGY
Francisco Epelde
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引用次数: 0

摘要

急性呼吸道感染(ARIs)是全球重大的健康负担,导致高发病率和高死亡率,尤其是在弱势人群中。诊断和跟踪急性呼吸道感染的传统方法往往在速度、准确性和可扩展性方面受到限制。人工智能(AI)的出现有可能通过加强早期检测、精确诊断和有效的流行病学跟踪来彻底改变这些过程。本综述探讨了人工智能与急性呼吸道感染流行病学和诊断的整合,重点介绍了人工智能的能力、当前应用和未来前景。通过研究最新进展和现有研究,本文全面阐述了人工智能如何改善急性呼吸道感染管理,深入探讨了人工智能的实际应用以及为充分发挥其潜力而必须应对的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How AI Could Help Us in the Epidemiology and Diagnosis of Acute Respiratory Infections?

Acute respiratory infections (ARIs) represent a significant global health burden, contributing to high morbidity and mortality rates, particularly in vulnerable populations. Traditional methods for diagnosing and tracking ARIs often face limitations in terms of speed, accuracy, and scalability. The advent of artificial intelligence (AI) has the potential to revolutionize these processes by enhancing early detection, precise diagnosis, and effective epidemiological tracking. This review explores the integration of AI in the epidemiology and diagnosis of ARIs, highlighting its capabilities, current applications, and future prospects. By examining recent advancements and existing studies, this paper provides a comprehensive understanding of how AI can improve ARI management, offering insights into its practical applications and the challenges that must be addressed to realize its full potential.

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来源期刊
Pathogens
Pathogens Medicine-Immunology and Allergy
CiteScore
6.40
自引率
8.10%
发文量
1285
审稿时长
17.75 days
期刊介绍: Pathogens (ISSN 2076-0817) publishes reviews, regular research papers and short notes on all aspects of pathogens and pathogen-host interactions. There is no restriction on the length of the papers. Our aim is to encourage scientists to publish their experimental and theoretical research in as much detail as possible. Full experimental and/or methodical details must be provided for research articles.
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