Artificial Intelligence in Diagnosis and Management of Infectious Diseases: An Overview

Abstract

Artificial intelligence (AI) is rapidly evolving, and this has brought about revolutionary developments in a number of industries, most notably healthcare. This analysis highlights how AI has the ability to completely transform healthcare delivery by examining its crucial role in the detection and treatment of infectious diseases. AI technologies are enhancing the accuracy and efficiency of infectious disease diagnosis through machine learning, automated diagnostics, NLP, and predictive modeling. Machine learning excels in tasks like interpreting diagnostic imaging and analyzing genomic data for infections. NLP aids in extracting critical information from medical literature and health records for timely diagnoses. Predictive modeling helps forecast disease outbreaks, guiding public health interventions. AI-driven diagnostics enable rapid pathogen identification, while AI-enhanced Clinical Decision Support Systems (CDSS) improve treatment recommendations. In personalized medicine, AI tailors treatments based on patient data for better outcomes. AI also aids remote monitoring, especially during pandemics, and supports public health strategies like optimizing vaccination campaigns and targeted messaging. Despite these advancements, challenges such as data privacy, algorithmic bias, integration with existing healthcare systems, and regulatory concerns must be addressed. Future prospects for AI in infectious disease management are promising, with ongoing research and development focusing on enhancing AI capabilities and fostering multidisciplinary collaborations. These efforts are essential to harness the full potential of AI in transforming infectious disease management and improving global health outcomes.