01827nas a2200217   4500000000100000008004100001260002300042653003400065653002800099653002100127653002200148100002000170700001400190700001900204245008400223856007000307300000800377490000700385520119200392022002501584       2024                            d  bInforma UK Limited10ainfectious disease management10aArtificial Intelligence10aMachine learning10aBig data analytic1 aAl Meslamani AZ1 aSobrino I1 ade la Fuente J00aMachine learning in infectious diseases: potential applications and limitations  uhttps://www.tandfonline.com/doi/pdf/10.1080/07853890.2024.2362869  a1-90 v563 a<p>Infectious diseases are a major threat for human and animal health worldwide. Artificial Intelligence (AI) combined algorithms including Machine Learning and Big Data analytics have emerged as a potential solution to analyse diverse datasets and face challenges posed by infectious diseases. In this commentary we explore the potential applications and limitations of ML to management of infectious disease. It explores challenges in key areas such as outbreak prediction, pathogen identification, drug discovery, and personalized medicine. We propose potential solutions to mitigate these hurdles and applications of ML to identify biomolecules for effective treatment and prevention of infectious diseases. In addition to use of ML for management of infectious diseases, potential applications are based on catastrophic evolution events for the identification of biomolecular targets to reduce risks for infectious diseases and vaccinomics for discovery and characterization of vaccine protective antigens using intelligent Big Data analytics techniques. These considerations set a foundation for developing effective strategies for managing infectious diseases in the future.</p>
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