Data augmentation and multimodal learning for predicting drug response in patient-derived xenografts from gene expressions and histology images

1 code implementation • 25 Apr 2022 • Alexander Partin, Thomas Brettin, Yitan Zhu, James M. Dolezal, Sara Kochanny, Alexander T. Pearson, Maulik Shukla, Yvonne A. Evrard, James H. Doroshow, Rick L. Stevens

Prediction performance of three unimodal NNs which use GE are compared to assess the contribution of data augmentation methods.

Data Augmentation Drug Response Prediction +1

Converting tabular data into images for deep learning with convolutional neural networks

1 code implementation • Scientific Reports 2021 • Yitan Zhu, Thomas Brettin, Fangfang Xia, Alexander Partin, Maulik Shukla, Hyunseung Yoo, Yvonne A. Evrard, James H. Doroshow, Rick L. Stevens

Convolutional neural networks (CNNs) have been successfully used in many applications where important information about data is embedded in the order of features, such as speech and imaging.

Learning Curves for Drug Response Prediction in Cancer Cell Lines

1 code implementation • 25 Nov 2020 • Alexander Partin, Thomas Brettin, Yvonne A. Evrard, Yitan Zhu, Hyunseung Yoo, Fangfang Xia, Songhao Jiang, Austin Clyde, Maulik Shukla, Michael Fonstein, James H. Doroshow, Rick Stevens

In contrast, a GBDT with hyperparameter tuning exhibits superior performance as compared with both NNs at the lower range of training sizes for two of the datasets, whereas the mNN performs better at the higher range of training sizes.

Drug Response Prediction

Ensemble Transfer Learning for the Prediction of Anti-Cancer Drug Response

no code implementations • 13 May 2020 • Yitan Zhu, Thomas Brettin, Yvonne A. Evrard, Alexander Partin, Fangfang Xia, Maulik Shukla, Hyunseung Yoo, James H. Doroshow, Rick Stevens

Previous transfer learning studies for drug response prediction focused on building models that predict the response of tumor cells to a specific drug treatment.

Drug Response Prediction Transfer Learning