Pinned Repositories
.github
energAI-fuses
HAIM
Python Open-source package to replicate the HAIM study available in: https://doi.org/10.1038/s41746-022-00689-4
MED3pa
Python Open-source package that ensures robust and reliable ML models deployments
MEDfl
Medomics Federated Learning repository
MEDimage
Python Open-source package for medical images processing and radiomics features extraction.
MEDimage-app
MEDimage is a user-friendly application that enables the extraction and analysis of radiomics features from medical images, integrating advanced machine learning models to enhance medical research.
MEDomics-UdeS-website
MEDomicsLab
MEDomicsTools
MEDomics-UdeS's Repositories
MEDomics-UdeS/MEDomicsTools
MEDomics-UdeS/energAI-fuses
MEDomics-UdeS/MEDomics-UdeS-website
MEDomics-UdeS/MEDomicsLab
MEDomics-UdeS/MED3pa
Python Open-source package that ensures robust and reliable ML models deployments
MEDomics-UdeS/MEDfl
Medomics Federated Learning repository
MEDomics-UdeS/MEDimage
Python Open-source package for medical images processing and radiomics features extraction.
MEDomics-UdeS/HAIM
Python Open-source package to replicate the HAIM study available in: https://doi.org/10.1038/s41746-022-00689-4
MEDomics-UdeS/MEDimage-app
MEDimage is a user-friendly application that enables the extraction and analysis of radiomics features from medical images, integrating advanced machine learning models to enhance medical research.
MEDomics-UdeS/.github
MEDomics-UdeS/MEDomicsLab-docs
Documentation for the MEDomicsLab App
MEDomics-UdeS/MEDprofiles
MEDomics-UdeS/POYM
MEDomics-UdeS/ThePetaleProject
This repository stores the code implemented to generate the results of our paper: Machine learning strategies to predict late adverse effects in childhood acute lymphoblastic leukemia survivors
MEDomics-UdeS/MEDimage-app-docs
MEDomics-UdeS/predict-immunotherapy-response
This project contains the code which predicts response to immune checkpoint inhibition treatment from biomarkers of patients suffering from cancers. The goal is to highlight the predictive property of mutational signatures in immune checkpoint inhibition treatment.