DRIVE: Machine Learning to Identify Drivers of Cancer with High-Dimensional Genomic Data & Imputed Labels

no code implementations • 2 May 2021 • Adnan Akbar, Andrey Solovyev, John W Cassidy, Nirmesh Patel, Harry W Clifford

Identifying the mutations that drive cancer growth is key in clinical decision making and precision oncology.

BIG-bench Machine Learning Decision Making

Effective Sub-clonal Cancer Representation to Predict Tumor Evolution

no code implementations • 28 Nov 2019 • Adnan Akbar, Geoffroy Dubourg-Felonneau, Andrey Solovyev, John W Cassidy, Nirmesh Patel, Harry W Clifford

Our proposed method is based on the intuition that if we can capture the true characteristics of sub-clones within a tumor and represent it in the form of features, a sophisticated machine learning algorithm can be trained to predict its behavior.

BIG-bench Machine Learning