一个用于肺炎图像分类的轻量级ResNet18-SAM模型实现，采用SH-DCGAN生成少类样本数据，解决了数据不平衡的问题，同时结合剪枝策略实现轻量化！MedGAN-ResLite-V2 Released! Stay tuned!❤

This project aims to detect pneumonia from chest X-ray images using a Convolutional Neural Network (CNN). The model is trained on a dataset of chest X-ray images and evaluated for its performance. The project is ongoing, and I aim to fine-tune the model in the future. If you are seeing this, it means I am still working on the project.

This project uses a deep learning model built with the TensorFlow Library to detect pneumonia in X-ray images. The model architecture is based on the EfficientNetB7 model, which has achieved an accuracy of approximately 97.12% (97.11538%) on our test data. This high accuracy rate is one of the strengths of our AI model.

Enhancing medical image classification accuracy using GANs to generate synthetic datasets. By training a GAN to create realistic medical images, the project aims to overcome limitations of traditional data augmentation methods, ultimately improving classification accuracies for tasks like detecting pneumonia in X-rays.

A Deep learning model to predict Pneumonia and determine the location on the Chest X-Ray image

Automated Diagnosis of Pneumonia from Classification of Chest X-Ray Images using EfficientNet

A pytorch reimplementation of CheXNet

The proposed system uses machine learning to classify X-ray images for potential pneumonia diagnosis. Designed to enhance accuracy and speed, it aims to supplement traditional radiologist evaluations, reducing human error and ensuring timely detection of this critical health concern.

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

MDPD - Microbiome Database of Pulmonary Diseases

Heatmap showing the number of deaths month to month since the beginning of the pandemic.

This research paper explores the use of deep convolutional neural networks for detecting pneumonia in medical imaging data.

The following study presents a model for generating chest X-ray images of normal subjects (without lung disease) and pneumonia patients.

Projeto de machine learning para predição óbitos de pacientes internados por pneumonia.

CXR-ACGAN: Auxiliary Classifier GAN (AC-GAN) for Chest X-Ray (CXR) Images Generation (Pneumonia, COVID-19 and healthy patients) for the purpose of data augmentation. Implemented in TensorFlow, trained on COVIDx CXR-3 dataset.

Diagnosis of pneumonia based on x-ray images

CS404 Artificial Intelligence final project. This project is based on the Pneumonia Images dataset found on Kaggle. The goal was to classify the images using classic Artificial Neural Networks.

This is a flask app that analyzes an X-ray and predicts if someone has TB/pneumonia.

A Web Application that can Detect Pneumonia from Chest X-ray images.