Molecular Pathogens 2024, Vol.15, No.1, 1-8 http://microbescipublisher.com/index.php/mp 1 Research Article Open Access Application of Artificial Intelligence in Early Diagnosis of Influenza A (H1N1) Virus Infection ShaLi Ningbo cha microorganism technology co., ltd, Ningbo, 315000, Zhejiang, China Corresponding email: Judyzhouww@163.com Molecular Pathogens, 2024, Vol.15, No.1 doi: 10.5376/mp.2024.15.0001 Received: 27 Dec., 2024 Accepted: 30 Dec., 2024 Published: 01 Jan., 2024 Copyright © 2024 Li, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Li S., 2024, Application of artificial intelligence in early diagnosis of influenza A (H1N1) virus infection, Molecular Pathogens, 15(1): 1-8 (doi: 10.5376/mp.2024.15.0001) Abstract This review mainly discusses the application and potential value of artificial intelligence in early diagnosis of influenza A (H1N1) virus infection. By comparing the advantages and disadvantages of the commonly used influenza A (H1N1) virus diagnosis methods, the limitations of the diagnosis methods and the wide applicability of artificial intelligence in medical diagnosis, this paper focuses on the specific application of artificial intelligence in the diagnosis of influenza A (H1N1) virus infection, and highlights its special advantages in improving the accuracy and efficiency of early diagnosis. The research also discusses the advantages and challenges of how artificial intelligence can improve the accuracy and efficiency of early diagnosis. In addition, this review also summarizes the future development trend of artificial intelligence in early diagnosis of influenza A (H1N1) virus infection. Through practical application and case study, the effect and influence of artificial intelligence in practical application are evaluated, and suggestions and prospects for future research are put forward. Although artificial intelligence still faces some challenges and limitations in practical application, with the continuous progress of technology and deeper understanding of artificial intelligence, it is believed that the application of artificial intelligence in medical and health fields will be more and more extensive in the future. Keywords Artificial intelligence; Early diagnosis; Influenza A (H1N1) virus; Effect evaluation 1 Introduction The influenza A (H1N1) virus is a highly contagious virus that has become one of the significant global public health threats since its first outbreak in 2009. The disease symptoms caused by the virus are similar to other types of influenza, including fever, cough, sore throat, and body aches. However, it can also lead to more severe complications such as pneumonia and respiratory failure. Therefore, early diagnosis of influenza A (H1N1) virus infection is crucial for controlling the spread of the epidemic and timely treatment of patients. This study will explore the application of artificial intelligence in the early diagnosis of influenza A (H1N1) virus infection, analyzing its feasibility and potential value (María et al., 2021). The application of artificial intelligence in medical diagnosis has become one of the hot topics in research nowadays. It involves various technologies such as machine learning, deep learning, and natural language processing, which can handle large amounts of medical data and improve the accuracy and efficiency of diagnosis. In medical diagnosis, the application of artificial intelligence can support doctors in tasks such as disease analysis, prediction, and treatment plan formulation. Particularly in the face of outbreaks of novel viruses, artificial intelligence can assist doctors in quickly identifying suspected cases, implementing early isolation and treatment measures, and effectively preventing the spread of the virus (Mintz and Brodie, 2018). By studying and analyzing the application of artificial intelligence in the early diagnosis of influenza A (H1N1) virus infection, this research aims to validate the potential of artificial intelligence in improving diagnostic accuracy and efficiency, and explore its practical effects in practice (Lin et al., 2021). It is believed that through the application of artificial intelligence technology, cases of influenza A (H1N1) virus infection can be diagnosed faster and more accurately in the future, thus gaining valuable time for prevention, control, and treatment efforts, and effectively safeguarding public health and safety.
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