| 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 | 209 | 2017 |
| 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), 1613, 2021 | 149 | 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 74 (1), 133-147, 2021 | 129 | 2021 |
| 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 | 95 | 2016 |
| Deep learning-based assessment of tumor-associated stroma for diagnosing breast cancer in histopathology images BE Bejnordi, J Lin, B Glass, M Mullooly, GL Gierach, ME Sherman, ... 2017 IEEE 14th international symposium on biomedical imaging (ISBI 2017 …, 2017 | 89 | 2017 |
| Methodological issues in predicting pediatric epilepsy surgery candidates through natural language processing and machine learning KB Cohen, B Glass, HM Greiner, K Holland-Bouley, S Standridge, R Arya, ... Biomedical informatics insights 8, BII. S38308, 2016 | 76 | 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, 1-22, 2015 | 58 | 2015 |
| 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 | 53 | 2019 |
| 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 | 42 | 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, 1-9, 2017 | 40 | 2017 |
| Association of artificial intelligence-powered and manual quantification of programmed death-ligand 1 (PD-L1) expression with outcomes in patients treated with nivolumabħipilimumab V Baxi, G Lee, C Duan, D Pandya, DN Cohen, R Edwards, H Chang, J Li, ... Modern Pathology 35 (11), 1529-1539, 2022 | 17 | 2022 |
| Continuous measurement of breast tumour hormone receptor expression: a comparison of two computational pathology platforms TP Ahern, AH Beck, BA Rosner, B Glass, G Frieling, LC Collins, ... Journal of clinical pathology 70 (5), 428-434, 2017 | 16 | 2017 |
| 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 | 11 | 2019 |
| Methodological issues in predicting pediatric epilepsy surgery candidates through natural language processing and machine learning. Biomed Inform Insights. 2016; 8: 11–8 KB Cohen, B Glass, HM Greiner, K Holland-Bouley, S Standridge, R Arya, ... | 11 | |
| Developing Expertise in 1H NMR Spectral Interpretation MC Connor, BH Glass, SA Finkenstaedt-Quinn, GV Shultz The Journal of Organic Chemistry 86 (2), 1385-1395, 2020 | 9 | 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, 2020.08. 02.233197, 2020 | 9 | 2020 |
| Development of the NMR Lexical Representational Competence (NMR-LRC) Instrument As a Formative Assessment of Lexical Ability in 1H NMR Spectroscopy MC Connor, BH Glass, GV Shultz Journal of Chemical Education 98 (9), 2786-2798, 2021 | 7 | 2021 |
| Machine Learning Models Identify Novel Histologic Features Predictive of Clinical Disease Progression in Patients with Advanced Fibrosis due to NASH H Pokkalla, B Glass, L Han, R Huss, K Kersey, GM Subramanian, ... 춘· 추계 학술대회 (The Liver Week) 2020 (1), 248-249, 2020 | 6 | 2020 |
| 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 | 5 | 2021 |
| 821 machine learning models can quantify cd8 positivity in lymphocytes in melanoma clinical trial samples B Glass, SA Stanford-Moore, D Meghwal, N Agrawal, M Lin, C Hedvat, ... Journal for ImmunoTherapy of Cancer 9 (Suppl 2), A859-A859, 2021 | 4 | 2021 |
