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

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第一作者： Alexander,Partin

第一单位： Division of Data Science and Learning, Argonne National Laboratory, Lemont, IL, United States.

作者： Alexander,Partin ^[1] ; Thomas,Brettin ^[1] ; Yitan,Zhu ^[1] ; James M,Dolezal ^[2] ; Sara,Kochanny ^[2] ; Alexander T,Pearson ^[2] ; Maulik,Shukla ^[1] ; Yvonne A,Evrard ^[3] ; James H,Doroshow ^[4] ; Rick L,Stevens ^[5]

作者单位： Division of Data Science and Learning, Argonne National Laboratory, Lemont, IL, United States. ^[1] Section of Hematology/Oncology, Department of Medicine, University of Chicago Medical Center, Chicago, IL, United States. ^[2] Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, MD, United States. ^[3] Division of Cancer Therapeutics and Diagnosis, National Cancer Institute, Bethesda, MD, United States. ^[4] Division of Data Science and Learning, Argonne National Laboratory, Lemont, IL, United States.;Department of Computer Science, The University of Chicago, Chicago, IL, United States. ^[5]

关键词 data augmentation drug response prediction gene expression histology whole-slide images multimodal deep learning patient-derived xenograft (PDX)preclinical drug studies

DOI 10.3389/fmed.2023.1058919

PMID 36960342

发布时间 2024-06-28

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

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

Frontiers in medicine

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Frontiers in medicine

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