Validating Machine Learning in Diagnostics

This chapter explores the role of machine learning as a diagnostic tool, particularly in diabetic eye diseases like diabetic retinopathy, focusing on the need for sensitivity over specificity. It emphasizes the importance of independent validation using diverse patient datasets to ensure the models' robustness and generalizability. The discussion highlights the complexities of validating machine learning algorithms, contrasting them with traditional diagnostic testing methods.