A Cross Layer Approach for Early Detection of Fibrous Dysplasia Using Feature Fusion and Graph Convolutional Neural Networks

Abstract

The application of deep learning has improved medical data analytics by producing cutting-edge results in a variety of applications because of its capacity to automatically understand complex patterns and representations from extensive medical datasets. Deep learning models can also help with precision medicine by predicting gene-disease connections, identifying genetic variations connected to diseases, and more. Convolutional neural networks (CNNs) are a popular choice for deep learning models when it comes to medical image analysis tasks including image segmentation, classification, and object detection. These models have shown exceptional performance in identifying anatomical structures, locating anomalies, and diagnosing diseases in a variety of medical imaging modalities newline