Nextflow Wrapper for TBProfiler

Tuberculosis (TB) remains a significant global health concern, ranking among the top ten causes of mortality worldwide. Timely and accurate detection of TB is pivotal for effective management and containment of the disease. In this study, we developed a robust TB detection system utilizing state-of-the-art methodologies including image preprocessor

This project is a Flask web application that integrates with TensorFlow a CNN model to be able to give predictions of two classes: "Normal" and "Tuberculosis". The user can upload their photo to be able to process it and also have a contrast enhancement filter applied with CLAHE.

Chest X-Rays Image Classification project from the course Applied AI in Biomedicine @ Politecnico di Milano

Developing a Tuberculosis Detection Application for the Omdena Myanmar Chapter

SDAIA's AI Bootcamp project. Tuberculosis detection.

Masters Project: Logistic Regression Analysis, Comparing the Completion of Latent Tuberculosis Therapy of HIV-Coinfected Individuals and Other Chronic High Risk Groups

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.

This repository contains tuberculosis classification on Chest X-ray using transfer learning in pytorch

Lung segmentation for chest X-Ray images with ResUNet and UNet. In addition, feature extraction and tuberculosis cases diagnosis had developed.

This is a Machine Learning and Deep Learning project that can predict the chances of getting diseases like Heart_Failure, Diabetes, Malaria and Tuberculosis.

Tuberculosis X-ray Classification