College of Information Technology, University of Babylon discussed a master dissertation on the stages of predicting type 1 diabetes using machine learning methods by the postgraduate student, Mrs. Nour Ali Fadhel.

The dissertation aimed at building a model that predicts the progression of T1D with the highest possible accuracy and the least error as a result of selecting the most important genes (informational genes).

The dissertation demonstrated an introduction to chronic diabetes, as well as the reasons for its occurrence as a result of the destruction of beta cells in the pancreas, which secretes a small amount of insulin or does not secrete it at all and the body uses blood sugar (glucose) to generate energy and enters the cells of the body through the hormone insulin.

The dissertation concluded that the performance of the proposed system is effective and the prediction accuracy was (0.100) four times from the sequential part of the classification models and once from random forests.