Detection Of Virus Using Ai And Ml Concepts
Anirudh Anirudh, Dr. Amandeep, Deepak Kumar, P. Anjani Mrs. N. Baby Rani, Satbir Satbir · International Journal of Research Publication and Reviews · 2025
Viruses are one of the most persistent and flexible pathogens that pose a threat to global health, and the most recent cases of such an outbreak, such as COVID-19, demonstrate that there is an extremely strong need in rapid detection and intervention strategies.This study explores an extensive virological map looking at some important viral families such as Influenza virus family, Herpesviruses, Coronaviruses, Papillomviruses, Enteroviruses, among others, their structure, mode of transmission, symptoms and ways of treatment.One of the major areas of interest of the work is the use of Artificial Intelligence (AI) technology, and especially deep learning algorithms, to improve virus identification and detection.Based on the utilization of the most sophisticated convolutional neural networks, including VGG19, ResNet50, U-Net, and the Truncated Inception Net, the study shows a high level of diagnostic accuracy in chest X-rays and CT imagings.A particular focus is made upon the spike proteins and the mechanisms of fusion that SARS-CoV-2 and Human Metapneumovirus (HMPV) activate and discuss their molecular nature, their path of infection, and possible AI-enhanced predictive modeling.The report is also concerned with virology and the viral morphogenesis; structural biology, and development of therapies, all which explain how AI is transforming virology, as a predictor and designer of outbreaks, vaccines, etc.It is a multidisciplinary study demonstrating the transformative nature of convergence research to fight existing and emerging virus threats with efficiency and greater accuracy via machine learning-powered virology.