Machine Learning in Medical Imaging

This chapter delves into the powerful ability of machine learning to analyze color fundus photographs for age prediction, validating its accuracy and exploring the eye's physiological changes with age. It also scrutinizes the challenges in understanding predictive mechanisms, using dermatology as a case study to illustrate potential pitfalls in model training. Emphasizing the critical need for proper image selection and validation studies, the chapter discusses the implications for applying these models in clinical settings.