Exploring Medical Diagnosis Using Vision Transformer And CNN

This research aims to conduct a comparative analysis of Vision Transformer (ViT) and Convolutional Neural Network (CNN) models for detecting four prevalent diseases: eye diseases, lung diseases, skin diseases, and heart diseases. The primary goal is to identify the most suitable and efficient model for each disease, taking into account their unique characteristics and diagnostic requirements. Through a meticulous evaluation and comparison of the performance of various ViT and CNN models for each illness, this study endeavors to offer valuable insights into the optimal utilization of these advanced technologies in disease detection. The comprehensive analysis presented in this paper is intended to contribute to the progress of medical imaging and potentially enhance diagnostic precision and efficacy in healthcare.