AI-based pathology predicts origins for cancers of unknown primary - Nature

A unified downloader+preprocessor for cancer genomics datasets

Discovering de novo shared transcriptional programs in single cancer cells

Some accessible radiomics datas were provided in this link.

Data analysis scripts for Rendeiro et. al, 2016 (doi:10.1038/ncomms11938)

Classifying Breast Cancer Molecular Subtypes

An example of predicting breast cancer using existing data to learn with decision trees (scikit-learn/python)

An automated lung cancer detection project.

More detailed growth models using inference.

DeepResponse: Large Scale Prediction of Cancer Cell Line Drug Response with Deep Learning Based Pharmacogenomic Modelling

Using Deep Learning to enhance cancer treatment. Project presented at the 2018 Startupfest hackathon.

Building a machine learning project named Breast Cancer Classification using Python 3.6, IPython Notebook and Python Virtual Environment

Identification of cancer-causing variants

A Markov Decision Process with large number of states and its solvers (value iteration, policy iteration and Q-learning)

A machine-learning model that uses a convolutional neural network to classify lung tumors in CT scans, which will help detect lung tumors that might have went unnoticed

Repository for Cancer Disease Response Inference

Deep learning model to distinguish cancer-associated T cell receptors from non-cancer ones

A dashboard for exploring research results

This repository houses a workflow that uses biological feature trees to segregate cancer RNA-seq datasets, then it trains machine learning models to predict the presence or absence of known, cancer-associated DNA-level mutations.

Mutation Detection in Lung Cancer Cell Lines using CNNs