{"title":"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?","authors":"Francisco Epelde","doi":"10.3390/pathogens13110940","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":19758,"journal":{"name":"Pathogens","volume":"13 11","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11597561/pdf/","citationCount":"0","resultStr":"{\"title\":\"How AI Could Help Us in the Epidemiology and Diagnosis of Acute Respiratory Infections?\",\"authors\":\"Francisco Epelde\",\"doi\":\"10.3390/pathogens13110940\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":19758,\"journal\":{\"name\":\"Pathogens\",\"volume\":\"13 11\",\"pages\":\"\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2024-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11597561/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pathogens\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3390/pathogens13110940\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pathogens","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3390/pathogens13110940","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MICROBIOLOGY","Score":null,"Total":0}
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.
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.