Sha Li

Ningbo cha microorganism technology co., ltd, Ningbo, 315000, China
Author    Correspondence author
Molecular Pathogens, 2024, Vol. 15, No. 1   doi: 10.5376/mp.2024.15.0001
Received: 27 Dec., 2023    Accepted: 28 Dec., 2023    Published: 01 Jan., 2024

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.

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)

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.

Artificial intelligence; Early diagnosis; Influenza A (H1N1) virus; Effect evaluation