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2020 – today
- 2022
[j3]Parmida Ghahremani, Yanyun Li, Arie E. Kaufman, Rami Vanguri, Noah Greenwald
, Michael Angelo, Travis J. Hollmann, Saad Nadeem:
Deep learning-inferred multiplex immunofluorescence for immunohistochemical image quantification. Nat. Mach. Intell. 4(4): 401-412 (2022)- 2021
- [j2]Yu-Cheng Liu, Yulin Liu, Rami Vanguri, Daniel Litwiller, Michael Z. Liu, Hao-Yun Hsu, Richard Ha, Hiram Shaish, Sachin Jambawalikar:
3D Isotropic Super-resolution Prostate MRI Using Generative Adversarial Networks and Unpaired Multiplane Slices. J. Digit. Imaging 34(5): 1199-1208 (2021) - 2020
- [j1]Michael Z. Liu, Rami Vanguri, Simukayi Mutasa, Richard Ha, Yu-Cheng Liu, Terry Button, Sachin Jambawalikar:
Channel width optimized neural networks for liver and vessel segmentation in liver iron quantification. Comput. Biol. Medicine 122: 103798 (2020) - [c6]Andrew Aukerman, Mathieu Carrière, Chao Chen, Kevin Gardner, Raúl Rabadán, Rami Vanguri:
Persistent Homology Based Characterization of the Breast Cancer Immune Microenvironment: A Feasibility Study. SoCG 2020: 11:1-11:20
2010 – 2019
- 2018
- [c5]Phyllis M. Thangaraj, Fernanda C. Polubriaginof, Benjamin Kummer, Rami Vanguri, Tal Lorberbaum, Joseph D. Romano, Kayla Quinnies, Alexandre Yahi, Mitchell S. V. Elkind, Nicholas P. Tatonetti:
Using model classifications as quantitative traits to estimate stroke heritability. AMIA 2018 - [c4]Ahana Roy Choudhury, Rami Vanguri, Sachin R. Jambawalikar, Piyush Kumar:
Segmentation of Brain Tumors Using DeepLabv3+. BrainLes@MICCAI (2) 2018: 154-167 - 2017
- [c3]Kenrick Cato, Joseph D. Romano, Rami Vanguri, Nicholas P. Tatonetti:
The Use of Informatics to Reduce Disparities in Transgender Health. AMIA 2017 - [c2]Joseph D. Romano, Kenrick Cato, Rami Vanguri, Nicholas P. Tatonetti:
Deep recurrent neural networks identify transgender patients. AMIA 2017 - [c1]Fernanda Polubriaginof, Kayla Quinnies, Rami Vanguri, Alexandre Yahi, Mary Simmerling, Iuliana Ionita-Laza, Hojjat Salmasian, Suzanne Bakken, George Hripcsak, Krzysztof Kiryluk, David Goldstein, Nicholas P. Tatonetti, David K. Vawdrey:
Automated Identification of Families in Electronic Health Records to Support Clinical Research. CRI 2017 - [i1]Alexandre Yahi, Rami Vanguri, Noémie Elhadad, Nicholas P. Tatonetti:
Generative Adversarial Networks for Electronic Health Records: A Framework for Exploring and Evaluating Methods for Predicting Drug-Induced Laboratory Test Trajectories. CoRR abs/1712.00164 (2017)
Coauthor Index
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last updated on 2024-04-24 22:56 CEST by the dblp team
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