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J

Jacqueline A. Brosnan-Cashman

Wake Forest University
H指数:19
被引数:2,283

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Spatial Mapping of Gene Signatures in Hematoxylin and Eosin-Stained Images: A Proof of Concept for Interpretable Predictions Using Additive Multiple Instance Learning

苏木精和伊红染色图像中基因特征的空间映射:一种基于加性多重实例学习的可解释预测的概念验证

2025-05-150
OAAI
A feasibility study using quantitative and interpretable histological analyses of celiac disease for automated cell type and tissue area classification

使用乳糜泻的定量和可解释的组织学分析进行自动细胞类型和组织区域分类的可行性研究

2024-12-020
OAAI
AI powered quantification of nuclear morphology in cancers enables prediction of genome instability and prognosis
2024-06-190
OAAI
AI-based quantitation of cancer cell and fibroblast nuclear morphology reflects transcriptomic heterogeneity and predicts survival in breast cancer
2023-03-010
PRE
Quantitative analysis of fiber-level collagen features in H&E whole-slide images predicts neoadjuvant therapy response in patients with HER2+breast cancer
2023-03-010
PRE
IDENTIFICATION OF CLINICALLY RELEVANT SPATIAL TISSUE PHENOTYPES IN LARGE-SCALE MULTIPLEX IMMUNOFLUORESCENCE DATA VIA UNSUPERVISED GRAPH LEARNING IN NON-SMALL CELL LUNG CANCER
2022-11-070
OA
ATRX loss in glioma results in dysregulation of cell-cycle phase transition and ATM inhibitor radio-sensitization
2022-01-0142
OA