Loading...
A deep learning framework for predicting response to therapy in cancer
Sakellaropoulos, T Vougas, K Narang, S Koinis, F Kotsinas, A Polyzos, A Moss, TJ Piha-Paul, S Zhou, H Kardala, E
Sakellaropoulos, T
Vougas, K
Narang, S
Koinis, F
Kotsinas, A
Polyzos, A
Moss, TJ
Piha-Paul, S
Zhou, H
Kardala, E
Citations
Altmetric:
Abstract
A major challenge in cancer treatment is predicting clinical response to anti-cancer drugs on a personalized basis. Using a pharmacogenomics database of 1,001 cancer cell lines, we trained deep neural networks for prediction of drug response and assessed their performance on multiple clinical cohorts. We demonstrate that deep neural networks outperform the current state in machine learning frameworks. We provide a proof of concept for the use of deep neural network-based frameworks to aid precision oncology strategies.
Authors
Description
Date
2019
Publisher
Collections
Files
Loading...
From UNPAYWALL
Adobe PDF, 3.21 MB
Keywords
Type
Article
Citation
Sakellaropoulos T, Vougas K, Narang S, Koinis F, Kotsinas A, Polyzos A, et al. A Deep Learning Framework for Predicting Response to Therapy in Cancer. Cell Rep. 2019;29(11):3367-73 e4.