College of Science at the University of Diyala discussed a master dissertation on diagnosing of celiac disease based on biopsy images using deep learning techniques by the postgraduate student, Ms. Israa Ali Abbas>

The dissertation aimed at developing an artificial intelligence model based on deep learning techniques to analyze tissue biopsy images with high accuracy and efficiency, contributing to accelerate the diagnosis of celiac disease and supporting medical decisions.

The dissertation included the use of a database containing thousands of processed tissue images, training deep models such as ResNet-50 and developing methods to improve model accuracy and overcome the problem of data imbalance.

The dissertation reviewed that the proposed model achieved an accuracy of 74.99%, outperforming traditional models such as VGG16 and InceptionV3, highlighting the potential of relying on artificial intelligence techniques as a tool to assist physicians.

The dissertation confirmed that the proposed model achieved an accuracy of 74.99%, outperforming traditional models such as VGG16 and InceptionV3, highlighting the potential of relying on artificial intelligence techniques as a tool to assist physicians.