Enhancing Diagnostic Precision through AI in Medical Imaging: A Comprehensive Review of Advances and Challenges

Abstract

Medical imaging-assisted diagnosis plays a vital role in modern healthcare by enabling visualization and analysis of internal body structures. However, the traditional interpretation of medical images is often time-consuming and prone to human error, potentially delaying diagnosis and treatment. Artificial intelligence (AI) offers promising solutions to enhance the speed, accuracy, and efficiency of diagnostic processes. This review paper provides a comprehensive overview of recent AI advancements in medical imaging-assisted diagnosis, exploring various algorithms and techniques developed to support clinical decision-making. It also addresses key challenges, including ethical concerns and limitations of current AI applications in clinical settings. The paper emphasizes the importance of refining AI models tailored for medical imaging to ensure seamless integration into healthcare workflows. Finally, it highlights emerging trends and future research directions aimed at maximizing the impact of AI on diagnostic precision and improving patient outcomes.