# Medical Image Recognition

A zero-shot image classification model based on the open_clip library, specializing in medical field image analysis

This model is a fine-tuned version of Google's ViT base model on a brain tumor image dataset, designed for brain tumor image classification tasks, achieving a test set accuracy of 93.16%.

This is an image classification model for dental health status, capable of identifying three states: healthy teeth, missing teeth, and cavities.

A PyTorch-based image classification model for dental health status recognition