AI-Powered Diagnosis: A New Weapon Against Cancer and Microbial Infections

Artificial Intelligence (AI) has emerged as a transformative tool in computational biology, enabling unprecedented advancements in medical diagnostics and research. AI efficiently processes and analyzes large, complex datasets, uncovering intricate patterns in genomics, proteomics, and clinical records. This review explores the applications of AI in diagnosing bacterial infections and cancer, highlighting its potential to revolutionize personalized medicine. Breakthroughs such as AlphaFold in structural biology, AI-driven drug discovery, and enhanced imaging techniques underscore AI’s impact on healthcare. AI has advanced microbial diagnostics, enabling rapid identification and characterization of pathogens, antimicrobial resistance genes, and disease markers. Similarly, in oncology, AI tools excel in early cancer detection, prognosis prediction, and patient stratification, improving outcomes and reducing mortality rates. However, challenges such as bias in datasets, lack of interpretability, and integration hurdles within clinical workflows persist. This article reviews current advancements, clinical applications, and limitations of AI in medical diagnostics, offering insights into future directions for its development and integration into healthcare systems. Addressing these challenges will be crucial to maximizing AI's potential to enhance diagnostic accuracy, reduce disparities, and improve global health outcomes.