The impact of clinical history on the predictive performance of machine learning and deep learning models for renal complications of diabetes.
Journal:
Computer methods and programs in biomedicine
Published Date:
Aug 1, 2025
Abstract
BACKGROUND AND OBJECTIVE: Diabetes is a chronic disease characterised by a high risk of developing diabetic nephropathy. The early identification of individuals at heightened risk of such complications or their exacerbation can be crucial to set a correct course of treatment. However, there are currently no widely accepted predictive tools for this task and, additionally, most of these models rely only on information at a single baseline visit. Considering this, we investigate the potential predictive role of patients' clinical history over multiple levels of renal disease severity while, at the same time, developing an effective predictive model.