Name: NKI AI for Oncology Lab
Type: Organization
Bio: The AI for Oncology Lab's mission to is to develop AI innovations which improve cancer diagnosis and therapy.
Twitter: AI4Oncology
Location: Netherlands
Blog: https://aiforoncology.nl
NKI AI for Oncology Lab's Projects
Ahcore is the AI for Oncology core computational pathology toolkit
Ahcore are the AI for Oncology histopathology core models
Open source code for AlphaFold.
Forked ansible nvidia driver role compatible with ubuntu 22
Constrained Empirical Risk Minimization
Python utilities to prevent over usage of resources by cluster users
:alarm_clock: AI for oncology conference deadline countdowns
Neural networks for cryo-EM reconstruction
Tools to parse large DICOM database to formats suitable for deep learning
DICOM Toolkit (dicomtk) is a Python library that parses a variety of dicom files into an SQLite database and can export to other formats.
Deep learning framework for MRI reconstruction
Dlup are the Deep Learning Utilities for Pathology developed at the Netherlands Cancer Institute
dlup-lightning-mil is an installable repo to easily train deep learning classifiers/regressors on gigapixel histopathology images using DLUP datasets or extracted features from HISSL
A PyTorch implementation of the Exclusive Cross Entropy Loss.
Histology Self-Supervised Learning
HistoQC is an open-source quality control tool for digital pathology slides
A basic setup for automatic submission and tracking of large hyperparameter experiments. UvA Deep Learning 2 Course.
A simple CLI utility for computing the intra-tumoral stroma percentage biomarker from segmentations of histopathological tumor lesions.
Kandinsky conformal prediction for image segmentation algorithms
Repository for Kosmos Cluster
Tools for building GPU clusters
Documentation for the use of the internal AI for Oncology cluster Kosmos
Python utilities to manage the Kosmos cluster
Self-supervised learning of mammogram data