Medical imaging analysis plays a critical role in the medical field, transforming how diseases are found, diagnosed, and treated. The integration of machine learning and deep learning has dramatically advanced the field of medical image analysis, leading to the creation of more advanced algorithms for improved diagnosis and disease detection. This study examines the impact of these cutting-edge technologies on the accuracy of medical imaging analysis. It investigates the most effective algorithms and techniques currently used, as well as how different types of medical images impact the accuracy and efficiency of these algorithms. The limitations and challenges faced during implementation and their effect on healthcare professionals� decision-making are also explored. This research provides a comprehensive understanding of the state of the art in medical image analysis through machine learning and deep learning, highlighting recent developments and their practical applications. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.