Role of Artificial Intelligence in Radiology and Medical Imaging: Current Status and Future Prospects

Artificial Intelligence (AI) is rapidly transforming radiology and medical imaging by enhancing diagnostic accuracy, workflow efficiency, and patient care. AI applications, particularly deep learning and machine learning algorithms, can automatically detect, segment, and classify medical images, enabling faster interpretation and reducing human error. This paper examines the current status of AI integration in radiology, highlighting its use in detecting diseases such as cancer, cardiovascular disorders, and neurological conditions, as well as in image reconstruction and quality enhancement. The study also explores future prospects, including AI-driven predictive analytics, personalized imaging protocols, and fully automated radiology workflows. Challenges such as data privacy, algorithmic bias, regulatory approval, and integration into clinical practice are critically analyzed. Comparative evaluation of existing AI tools and frameworks underscores the potential of AI to augment radiologists rather than replace them, improving diagnostic confidence and patient outcomes. The paper concludes that continued research, collaboration between AI developers and healthcare professionals, and robust ethical and regulatory frameworks are essential to fully realize AI’s potential in medical imaging.