In this paper author is describing concept to detect eyes pediatric age genetic diseases using Pupillometry device data as this device is very accurate and it’s not require huge number of clinical test to detect disease. Overview This repository contains a machine learning model developed in Python for the automatic prediction of eye diseases using medical images. The model is trained on a diverse dataset and utilizes deep learning techniques for accurate and efficient disease classification.
Features Image Classification: The model classifies eye images into various disease categories, including diabetic retinopathy, glaucoma, and age-related macular degeneration (AMD).
Deep Learning: Built on a powerful convolutional neural network (CNN) architecture to extract complex features from input images, enabling accurate predictions.
Open Source: The project is open source, encouraging collaboration and contributions from the community.
Usage Clone the repository:
git clone https://github.com/srilekha-netha/eye-disease-prediction.git ##Dependencies pip install -r requirements.txt
Run the application python DiseaseDetection.py
Access the web interface at http://localhost:5000 and upload your eye images for predictions.