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

A unified downloader+preprocessor for cancer genomics datasets

Classifying Breast Cancer Molecular Subtypes

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

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

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

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

A command-line toolkit for summarizing, analyzing, and interpreting ChIP-Seq and RNA-Seq experiments, designed for enhancer and super-enhancer region analysis in tumor-normal pairs, with applications in differential enrichment and multi-sample domain analysis.

Detecting and Tracking cancer (HeLa) cells using Computer Vision techniques. The project also detects cell division and analyses cell motion such as speed, distance travelled etc. The project uses OpenCV3 for image processing.

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

Detecting various characteristics of glioblastoma using Deep Learning

Repository for Cancer Disease Response Inference

Nanoneedles Enable Spatiotemporal Lipidomics of Living Tissues

Software for the automated analysis of in cellulo high-throughput drug screening

NeoGuider, neoepitope detection using advanced feature engineering

Some accessible radiomics datas were provided in this link.

More detailed growth models using inference.

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.

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

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