| Comparing three notions of discrete Ricci curvature on biological networks M Pouryahya, J Mathews, A Tannenbaum arXiv preprint arXiv:1712.02943, 2017 | 35 | 2017 |
| Robust and Interpretable PAM50 Reclassification Exhibits Survival Advantage for Myoepithelial and Immune Phenotypes JC Mathews, S Nadeem, AJ Levine, M Pouryahya, JO Deasy, ... npj Breast Cancer 5 (1), 2019 | 30 | 2019 |
| Characterizing cancer drug response and biological correlates: a geometric network approach M Pouryahya, JH Oh, JC Mathews, JO Deasy, AR Tannenbaum Scientific reports 8 (1), 6402, 2018 | 27 | 2018 |
| Functional network analysis reveals an immune tolerance mechanism in cancer JC Mathews, S Nadeem, M Pouryahya, Z Belkhatir, JO Deasy, AJ Levine, ... Proceedings of the National Academy of Sciences 117 (28), 16339-16345, 2020 | 22 | 2020 |
| A novel kernel Wasserstein distance on Gaussian measures: An application of identifying dental artifacts in head and neck computed tomography JH Oh, M Pouryahya, A Iyer, AP Apte, JO Deasy, A Tannenbaum Computers in biology and medicine 120, 103731, 2020 | 20 | 2020 |
| Multi stain graph fusion for multimodal integration in pathology C Dwivedi, S Nofallah, M Pouryahya, J Iyer, K Leidal, C Chung, T Watkins, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 16 | 2022 |
| aWCluster: A novel integrative network-based clustering of multiomics for subtype analysis of cancer data M Pouryahya, JH Oh, P Javanmard, JC Mathews, Z Belkhatir, JO Deasy, ... IEEE/ACM transactions on computational biology and bioinformatics 19 (3 …, 2020 | 15 | 2020 |
| Kernel wasserstein distance JH Oh, M Pouryahya, A Iyer, AP Apte, A Tannenbaum, JO Deasy arXiv preprint arXiv:1905.09314, 2019 | 14 | 2019 |
| Bakry-Émery Ricci curvature on weighted graphs with applications to biological networks M Pouryahya, R Elkin, R Sandhu, S Tannenbaum, T Georgiou, ... Int. Symp. on Math. Theory of Net. and Sys 22, 52, 2016 | 10 | 2016 |
| Pan-cancer prediction of cell-line drug sensitivity using network-based methods M Pouryahya, JH Oh, JC Mathews, Z Belkhatir, C Moosmüller, JO Deasy, ... International Journal of Molecular Sciences 23 (3), 1074, 2022 | 8 | 2022 |
| Molecular phenotyping using networks, diffusion, and topology: soft tissue sarcoma JC Mathews, M Pouryahya, C Moosmüller, YG Kevrekidis, JO Deasy, ... Scientific Reports 9 (1), 13982, 2019 | 8 | 2019 |
| Integration of deep learning-based histopathology and transcriptomics reveals key genes associated with fibrogenesis in patients with advanced NASH J Conway, M Pouryahya, Y Gindin, DZ Pan, OM Carrasco-Zevallos, ... Cell Reports Medicine 4 (4), 2023 | 5 | 2023 |
| AI-based histologic scoring enables automated and reproducible assessment of enrollment criteria and endpoints in NASH clinical trials JS Iyer, H Pokkalla, C Biddle-Snead, O Carrasco-Zevallos, M Lin, ... medRxiv, 2023 | 3 | 2023 |
| AI-based histologic measurement of NASH (AIM-NASH): a drug development tool for assessing clinical trial end points O Carrasco-Zevallos, A Taylor-Weiner, H Pokkalla, M Pouryahya, ... JOURNAL OF HEPATOLOGY 75, S254-S254, 2021 | 3 | 2021 |
| Liver biopsy graph neural networks for automated histologic scoring using the NASH CRN system J Wang, M Pouryahya, K Leidal, H Pokkalla, D Juyal, Z Shanis, A Pedawi, ... JOURNAL OF HEPATOLOGY 75, S602-S603, 2021 | 3 | 2021 |
| Stochastic norton–simon–massagué tumor growth modeling: Controlled and mixed-effect uncontrolled analysis Z Belkhatir, M Pavon, JC Mathews, M Pouryahya, JO Deasy, L Norton, ... IEEE Transactions on Control Systems Technology 29 (2), 704-717, 2020 | 3 | 2020 |
| Integration of machine learning-based histopathology and hepatic transcriptomic data identifies genes associated with portal inflammation and ductular proliferation as … M Pouryahya, AH Taylor-Weiner, H Pokkalla, K Pethia, H Elliott, BH Glass, ... The Liver Meeting Digital Experience™, 2020 | 3 | 2020 |
| A Novel Integrative Multiomics Method Reveals a Hypoxia-Related Subgroup of Breast Cancer with Significantly Decreased Survival M Pouryahya, JH Oh, P Javanmard, JC Mathews, Z Belkhatir, JO Deasy, ... bioRxiv, 558700, 2019 | 3 | 2019 |
| Exploratory analyses of NASH histology using CRN scores derived from a multi-stain machine learning method J Abel, C Dwivedi, S Nofallah, M Pouryahya, J Brosnan-Cashman, ... Hepatology 76, S69-S70, 2022 | 2 | 2022 |
| Reproducibility of radiomic features using network analysis and its application in Wasserstein k-means clustering JH Oh, AP Apte, E Katsoulakis, N Riaz, V Hatzoglou, Y Yu, U Mahmood, ... Journal of Medical Imaging 8 (3), 031904-031904, 2021 | 2 | 2021 |
Allen TannenbaumDistinguished Professor, Computer Science/Applied Mathematics, Stony Brook UniversityVerified email at stonybrook.edu
