Artificial Intelligence in Clinical Applications for Infectious Diseases: Diagnosis, Treatment and Immunization

Abstract

Infectious diseases continue to pose a significant threat to public health, despite significant advancements in science and technology over the last several years. These diseases have the potential to spread rapidly, posing serious health risks. They also affect 
whole communities and can even cause epidemics. The difficulty in making a quick and accurate diagnosis and the increase 
in antibiotic resistance have both added layers of complexity to the treatment of infectious diseases. Artificial intelligence has 
found practical use in several sectors, including the development of vaccines and anti-infective medications, the improvement 
of infection diagnosis and treatment methods, and the reduction of drug-resistant illnesses. There are a number of potential 
applications for clinical decision support systems that include AI. These include the prediction of disease outbreaks, the optimization of medication, the diagnosis of diseases, and the monitoring of epidemiological trends. Its improved speed and accuracy 
could potentially be useful for diagnosing illnesses and analyzing diagnostic images. For progress to be made in this field, a robust ethical framework and multidisciplinary research are essential. This review will touch on the history of artificial intelligence 
(AI) in the fight against infectious diseases, its current applications, and its potential future uses. We illustrate the benefits and 
applications of AI in the area of infectious diseases using real-world cases. This might lead to the development of more effective 
intervention strategies for the prevention and control of infectious diseases and the safeguarding of public health.