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In this paper, we developed a machine learning model ensemble approach consisting of a support vector machine (SVM), random forest (RF), Multilayer Perceptron (MLP), and Majority-VotingEnsemble classifiers.
This project uses deep learning algorithms and the Keras library to determine if a person has certain diseases or not from their chest x-rays and other scans. The trained model is displayed using Streamlit, which enables the user to upload an image and receive instant feedback.
Standardized Multi-Channel Dataset for Glaucoma (SMDG-19) is a collection and standardization of 19 public full-fundus glaucoma images and associated metadata.
Evaluation of a simple CNN model for glaucoma detection trained on a single public dataset against complex architectures trained on multiple public/private datasets