Use of Artificial Intelligence in Healthcare: A Comprehensive Review

Abstract

Artificial intelligence (AI) has emerged as a transformative force in healthcare, revolutionizing clinical practice, research, and patient care delivery. This review examines the current applications of AI across various healthcare domains, including medical imaging, diagnostics, drug discovery, personalized medicine, and healthcare administration. We discuss the integration of machine learning, deep learning, and natural language processing technologies that enable enhanced diagnostic accuracy, treatment optimization, and operational efficiency. The review highlights significant achievements in AI-powered medical imaging analysis, predictive analytics for disease progression, and clinical decision support systems. We also address critical challenges including data privacy concerns, algorithmic bias, regulatory frameworks, and the need for clinical validation. Despite these challenges, AI demonstrates substantial promise in addressing healthcare disparities, reducing clinician burnout, and improving patient outcomes. The future of AI in healthcare lies in developing explainable AI systems, ensuring equitable access, and fostering human-AI collaboration that augments rather than replaces clinical expertise.

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