Artificial Intelligence (AI) is increasingly reshaping the landscape of modern healthcare, offering transformative potential in patient care through enhanced diagnostics, personalized treatment, and improved clinical workflows. This systematic review explores the integration of AI technologies within healthcare systems, focusing on their impact on patient outcomes, operational efficiency, and clinical decision-making. Drawing from peer-reviewed literature, case studies, and clinical trials published over the past decade, this review categorizes AI applications into key domains including medical imaging, predictive analytics, robotic surgery, virtual health assistants, and electronic health records (EHR) optimization. The findings reveal that AI contributes significantly to early disease detection, risk stratification, treatment planning, and continuous patient monitoring. However, the review also highlights ongoing challenges such as data privacy concerns, algorithmic bias, lack of standardized regulations, and the need for interdisciplinary collaboration. Overall, this review underscores the pivotal role AI is playing in advancing patient care and outlines future directions for research and implementation in clinical practice.
KAMATCHI et al. (2025) studied this question.