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

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

Patient-derived xenografts (PDXs) are an appealing platform for preclinical drug studies. A primary challenge in modeling drug response prediction (DRP) with PDXs and neural networks (NNs) is the limited number of drug response samples. We investigate multimodal neural network (MM-Net) and data augm...

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Bibliographic Details
Main Authors: 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
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-03-01
Series:Frontiers in Medicine
Subjects:
drug response prediction
histology whole-slide images
gene expression
multimodal deep learning
preclinical drug studies
data augmentation
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2023.1058919/full

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https://www.frontiersin.org/articles/10.3389/fmed.2023.1058919/full

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