Molecular Pathogens 2024, Vol.15, No.1, 1-8 http://microbescipublisher.com/index.php/mp 8 The successful experience of artificial intelligence in the early diagnosis of influenza virus infection can provide inspiration for research on early diagnosis of other infectious diseases. Applying similar methods and techniques to the early diagnosis of other infectious diseases such as pneumonia, tuberculosis, etc., is expected to make greater progress in the prevention and control of infectious diseases. Conflict of Interest Disclosure The author affirms that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Benjamin H., Sumeet H., and Richard W. L., 2022, The role of artificial intelligence in early cancer diagnosis, Cancers, 14(6): 1524. https://doi.org/10.3390/cancers14061524 El Khatib M.M., and Ahmed G., 2019, Management of artificial intelligence enabled smart wearable devices for early diagnosis and continuous monitoring of CVDS, International Journal of Innovative Technology and Exploring Engineering, 9(1):1211-1215. https://doi.org/10.35940/ijitee.L3108.119119 Hegde S., Ajila V., Zhu W., and Zeng C.H., 2022, Artificial intelligence in early diagnosis and prevention of oral cancer, Asia-Pacific Journal of Oncology Nursing, 9(12): 100133. https://doi.org/10.1016/j.apjon.2022.100133 Huang S.G., Yang J., Fong S., and Zhao Q., 2020, Artificial intelligence in cancer diagnosis and prognosis: Opportunities and challenges, Cancer Letters, 471: 61-71. https://doi.org/10.1016/j.canlet.2019.12.007 Lee K.S., and Ahn K.H., 2020, Application of artificial intelligence in early diagnosis of spontaneous preterm labor and birth, Diagnostics, 10(9): 733. https://doi.org/10.3390/diagnostics10090733 Lin C., Lin C.S., Lee D.J., Lee C.C., Chen S.J., Tsai S.H. Kuo F.C., Chau T., and Lin S.H., 2021, Artificial intelligence-Assisted electrocardiography for early diagnosis of thyrotoxic periodic paralysis, Journal of the Endocrine Society, 5(9): 120. https://doi.org/10.1210/jendso/bvab120 María G.P., Eduardo P.F., Carlota S.F., Juan S.R., Amparo R.M., and Pia L.J., 2021, Role of artificial intelligence in the early diagnosis of oral cancer. A scoping review, Cancers, 13(18): 4600. https://doi.org/10.3390/cancers13184600 Michaelis M., Doerr H.W., and Cinatl Jr J., 2009, An influenza A H1N1 virus reviva l- pandemic H1N1/09 virus, Infection, 37: 381-389. https://doi.org/10.1007/s15010-009-9181-5 Mintz Y., and Brodie R., 2018, Introduction to artificial intelligence in medicine, Minimally Invasive Therapy & Allied Technologies, 28(2): 73-81. https://doi.org/10.1080/13645706.2019.1575882 Swine O., 2009, Emergence of a novel swine-origin influenza A (H1N1) virus in humans, N Engl J Med., 360: 2605-2615. https://doi.org/10.1056/NEJMoa0903810 Winter P., and Carusi A., 2022, Validation and the Co-Constitution of Trust in Developing Artificial Intelligence (AI) for the Early Diagnosis of Pulmonary Hypertension (PH), Science & Technology Studies, 35(4): 58-77. Yan W., Shi H., He T., Chen J., Wang C., Liao A.J., Yang W., and Wang H.H., 2021, Employment of artificial intelligence based on routine laboratory results for the early diagnosis of multiple myeloma, Front. Oncol., 11. https://doi.org/10.3389/fonc.2021.608191
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