Explainable and transparency machine learning approach to predict diabetes develop

This study aims to address the problem of type 1 diabetes by utilizing machine learning techniques and developing a decision support system based on Explainable Artificial Intelligence (XAI). The main research question is to predict the risk of developing type 1 diabetes in a population using different machine learning algorithms, while ensuring interpretability and transparency of the decision support system. The study builds upon a case-control study conducted by previous researchers, who approached the problem from a statistical-parametric perspective.