35 citations · 101 across the 12 of their papers we have counts for
5 papers · 1 filter
Deep learning methods for drug response prediction in cancer: predominant and emerging trends
Alexander Partin, Thomas S. Brettin, Yitan Zhu +4
Cancer claims millions of lives yearly worldwide. While many therapies have been made available in recent years, by in large cancer remains unsolved. Exploiting computational predi…
Data augmentation and multimodal learning for predicting drug response in patient-derived xenografts from gene expressions and histology images
Alexander Partin, Thomas Brettin, Yitan Zhu +7
Patient-derived xenografts (PDXs) are an appealing platform for preclinical drug studies because the in vivo environment of PDXs helps preserve tumor heterogeneity and usually bett…
A cross-study analysis of drug response prediction in cancer cell lines
Fangfang Xia, Jonathan Allen, Prasanna Balaprakash +21
To enable personalized cancer treatment, machine learning models have been developed to predict drug response as a function of tumor and drug features. However, most algorithm deve…
Learning Curves for Drug Response Prediction in Cancer Cell Lines
Alexander Partin, Thomas Brettin, Yvonne A. Evrard +9
Motivated by the size of cell line drug sensitivity data, researchers have been developing machine learning (ML) models for predicting drug response to advance cancer treatment. As…
Ensemble Transfer Learning for the Prediction of Anti-Cancer Drug Response
Yitan Zhu, Thomas Brettin, Yvonne A. Evrard +6
Transfer learning has been shown to be effective in many applications in which training data for the target problem are limited but data for a related (source) problem are abundant…