Benjamin Glass
Benjamin Glass
Harvard Medical School, Beth Israel Deaconess Medical Center
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Cited by
Cited by
Nanoscale imaging of clinical specimens using pathology-optimized expansion microscopy
Y Zhao, O Bucur, H Irshad, F Chen, A Weins, AL Stancu, EY Oh, ...
Nature biotechnology 35 (8), 757-764, 2017
The SIRT2 deacetylase stabilizes slug to control malignancy of basal-like breast cancer
W Zhou, TK Ni, A Wronski, B Glass, A Skibinski, A Beck, C Kuperwasser
Cell reports 17 (5), 1302-1317, 2016
Extensive rewiring of epithelial-stromal co-expression networks in breast cancer
EY Oh, SM Christensen, S Ghanta, JC Jeong, O Bucur, B Glass, ...
Genome biology 16 (1), 1-22, 2015
LINC00520 is induced by Src, STAT3, and PI3K and plays a functional role in breast cancer
WS Henry, DG Hendrickson, F Beca, B Glass, M Lindahl-Allen, L He, Z Ji, ...
Oncotarget 7 (50), 81981, 2016
EZH2 protein expression in normal breast epithelium and risk of breast cancer: results from the Nurses’ Health Studies
F Beca, K Kensler, B Glass, SJ Schnitt, RM Tamimi, AH Beck
Breast Cancer Research 19 (1), 1-9, 2017
Androgen receptor expression and breast cancer survival: results from the nurses’ health studies
KH Kensler, EM Poole, YJ Heng, LC Collins, B Glass, AH Beck, A Hazra, ...
JNCI: Journal of the National Cancer Institute 111 (7), 700-708, 2019
Human-interpretable image features derived from densely mapped cancer pathology slides predict diverse molecular phenotypes
JA Diao, JK Wang, WF Chui, V Mountain, SC Gullapally, R Srinivasan, ...
Nature communications 12 (1), 1-15, 2021
A machine learning approach enables quantitative measurement of liver histology and disease monitoring in NASH
A Taylor‐Weiner, H Pokkalla, L Han, C Jia, R Huss, C Chung, H Elliott, ...
Hepatology, 2021
Machine learning models accurately interpret liver histology in patients with nonalcoholic steatohepatitis (Nash)
H Pokkalla, K Pethia, B Glass, JK Kerner, Y Gindin, L Han, R Huss, ...
Hepatology 70, 121A-122A, 2019
CD8+ T cells in tumor parenchyma and stroma by image analysis (IA) and gene expression profiling (GEP): Potential biomarkers for immuno-oncology (IO) therapy.
PM Szabo, G Lee, S Ely, V Baxi, H Pokkalla, H Elliott, D Wang, B Glass, ...
Journal of Clinical Oncology 37 (15_suppl), 2594-2594, 2019
Abstract P5-02-02: Artificial intelligence powered predictive analysis of atypical ductal hyperplasia from digitized pathology images
JK Kerner, A Cleary, S Jain, H Pokkalla, B Glass, S Grossmith, M Harary, ...
Cancer Research 80 (4 Supplement), P5-02-02-P5-02-02, 2020
Validation of a machine learning-based approach (DELTA liver fibrosis score) for the assessment of histologic response in patients with advanced fibrosis due to NASH
AH Taylor-Weiner, H Pokkalla, L Han, C Jia, RS Huss, C Chung, H Elliott, ...
The Liver Meeting Digital Experience™, 2020
Dense, high-resolution mapping of cells and tissues from pathology images for the interpretable prediction of molecular phenotypes in cancer
JA Diao, WF Chui, JK Wang, RN Mitchell, SK Rao, MB Resnick, A Lahiri, ...
bioRxiv, 2020
Artificial intelligence-powered retrospective analysis of PD-L1 expression in nivolumab trials of advanced non-small cell lung cancer
V Baxi, A Beck, D Pandya, G Lee, C Hedvat, A Khosla, D Wang, H Elliott, ...
286P Artificial intelligence analysis of advanced breast cancer patients from a phase I trial of trastuzumab deruxtecan (T-DxD): HER2 and histopathology features as predictors …
S Modi, B Glass, A Prakash, A Taylor-Weiner, H Elliott, I Wapinski, ...
Annals of Oncology 31, S355-S356, 2020
Machine learning models identify novel histologic features predictive of clinical disease progression in patients with advanced fibrosis due to non-alcoholic steatohepatitis
H Pokkalla, K Pethia, A Taylor, B Glass, H Elliott, L Han, C Jia, R Huss, ...
Journal of Hepatology 73, S402, 2020
Machine learning-based identification of predictive features of the tumor micro-environment and vasculature in NSCLC patients using the IMpower150 study.
A Taylor-Weiner, A Beck, JD Cowan, H Elliott, J Fridlyand, B Glass, ...
Journal of Clinical Oncology 38 (15_suppl), 3130-3130, 2020
Machine learning fibrosis models based on liver histology images accurately characterize the heterogeneity of cirrhosis due to nonalcoholic steatohepatitis (NASH)
ZM Younossi, H Pokkalla, K Pethia, B Glass, JK Kerner, Y Gindin, L Han, ...
Hepatology 70, 1033A-1034A, 2019
Machine learning models to quantify HER2 for real-time tissue image analysis in prospective clinical trials.
B Glass, ME Vandenberghe, ST Chavali, SA Javed, M Rebelatto, ...
Journal of Clinical Oncology 39 (15_suppl), 3061-3061, 2021
Abstract PD6-04: Deep-learning based prediction of homologous recombination deficiency (hrd) status from histological features in breast cancer; a research study
A Taylor-Weiner, A Pedawi, WF Chui, J Diao, J Wang, V Mountain, ...
Cancer Research 81 (4 Supplement), PD6-04-PD6-04, 2021
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