Popular GitHub Repositories for Cancer

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening

BCDU-Net : Medical Image Segmentation

天池医疗AI大赛[第一季]：肺部结节智能诊断 UNet/VGG/Inception/ResNet/DenseNet

BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix

Cancer Imaging Phenomics Toolkit (CaPTk) is a software platform to perform image analysis and predictive modeling tasks. Documentation: https://cbica.github.io/CaPTk

Training and evaluating a variational autoencoder for pan-cancer gene expression data

A Machine Learning and Deep Learning based webapp used to predict multiple diseases.

[Nature Machine Intelligence 2024] Code and evaluation repository for the paper

BioDynaMo is a high-performance and modular, agent-based simulation platform.

Corresponding code of 'Quiros A.C., Murray-Smith R., Yuan K. Pathology GAN: Learning deep representations of cancer tissue. Proceedings of The 3rd International Conference on Medical Imaging with Deep Learning (MIDL) 2020'

Contextual Attention Network: Transformer Meets U-Net

Federated Learning based Deep Learning. Docs: https://fets-ai.github.io/Front-End/

Multiple disease prediction such as Diabetes, Heart disease, Kidney disease, Breast cancer, Liver disease, Malaria, and Pneumonia using supervised machine learning and deep learning algorithms.

This is the official repository for our CVPR 2023 paper 'Task-Specific Fine-Tuning via Variational Information Bottleneck for Weakly-Supervised Pathology Whole Slide Image Classification'.

TransDeepLab: Convolution-Free Transformer-based DeepLab v3+ for Medical Image Segmentation

Diseases Detection from NIH Chest X-ray data

Official release of MSHT: Multi-stage Hybrid Transformer for the ROSE Image Analysis of Pancreatic Cancer https://ieeexplore.ieee.org/document/10006398

Homomorphic Encryption and Federated Learning based Privacy-Preserving

Transfer Learning with DCNNs (DenseNet, Inception V3, Inception-ResNet V2, VGG16) for skin lesions classification

This application aims to early detection of lung cancer to give patients the best chance at recovery and survival using CNN Model.