We design a lightweight CNN architecture for the chest x-ray classi-32 fication task by introducing ExLNet which uses a novel DCISE blocks to reduce the33 computational burden. We show the effectiveness of the proposed architecture through34 various experiments performed on publicly available datasets.

This repository hosts code for a deep learning project focused on classifying chest X-ray images into normal and abnormal categories, with a specific emphasis on detecting COVID-19 and pneumonia cases. Leveraging convolutional neural networks (CNNs) and transfer learning methodologies, the project aims to achieve precise classification outcomes.

Convolutional AutoEncoder trained on VinBigData Chest X-ray dataset

Pneumonia detection from Chest-X-Ray images using Transfer Learning PyTorch, Flask, Docker, AWS.

Exploration of ML approaches for chest X-Ray image classification

[CMPB 2024] Attentional Decoder Networks for Chest X-ray Image Recognition on High-resolution Features

This is a repo for anyone wants to apply AI/DL in diagnosing diseases from Chest-Xray Images

A machine learning tool based on chest radiographs can aid radiologists or healthcare professionals in diagnosing COVID-19.

Pruning and fine-tuning for debiasing an already-trained neural network with applications to deep chest X-ray classifiers

Thoracic Disease Detection Using CNNs and Weighted Binary Cross Entropy Loss Based on Chest X-Ray Images

Works on Chest X-ray dataset.

Repository containing the code demonstrating a secure flow for Pneumonia detection using federated learning.

Convolutional Neural Network for Pneumonia and Covid-19 Detection in Chest X-Ray Images.

The Chest Cancer Classification project diagnoses chest cancer from medical images using deep learning. It integrates MLflow for experiment tracking, DVC for version control, and Flask for backend processing. Docker and a CI/CD pipeline with GitHub Actions and AWS.

This project is done as part of the Machine Learning subject in our curriculum.

An implementation of pix2pix GAN to improve Xray image quality