Rami Vanguri

According to our database, Rami Vanguri authored at least 10 papers between 2017 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

Deep learning-inferred multiplex immunofluorescence for immunohistochemical image quantification.

Parmida Ghahremani, Yanyun Li, Arie E. Kaufman, Rami Vanguri, Noah F. Greenwald, Michael Angelo, Travis J. Hollmann, Saad Nadeem

Nat. Mach. Intell., 2022

2021

3D Isotropic Super-resolution Prostate MRI Using Generative Adversarial Networks and Unpaired Multiplane Slices.

Yu-Cheng Liu, Yulin Liu, Rami Vanguri, Daniel Litwiller, Michael Z. Liu, Hao-Yun Hsu, Richard Ha, Hiram Shaish, Sachin Jambawalikar

J. Digit. Imaging, 2021

2020

Channel width optimized neural networks for liver and vessel segmentation in liver iron quantification.

Michael Z. Liu, Rami Vanguri, Simukayi Mutasa, Richard Ha, Yu-Cheng Liu, Terry Button, Sachin Jambawalikar

Comput. Biol. Medicine, 2020

Persistent Homology Based Characterization of the Breast Cancer Immune Microenvironment: A Feasibility Study.

Andrew Aukerman, Mathieu Carrière, Chao Chen, Kevin Gardner, Raúl Rabadán, Rami Vanguri

Proceedings of the 36th International Symposium on Computational Geometry, 2020

2018

Segmentation of Brain Tumors Using DeepLabv3+.

Ahana Roy Choudhury, Rami Vanguri, Sachin R. Jambawalikar, Piyush Kumar

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018

Using model classifications as quantitative traits to estimate stroke heritability.

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

Proceedings of the AMIA 2018, 2018

2017

Generative Adversarial Networks for Electronic Health Records: A Framework for Exploring and Evaluating Methods for Predicting Drug-Induced Laboratory Test Trajectories.

Alexandre Yahi, Rami Vanguri, Noémie Elhadad, Nicholas P. Tatonetti

CoRR, 2017

Automated Identification of Families in Electronic Health Records to Support Clinical Research.

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

Proceedings of the Summit on Clinical Research Informatics, 2017

Deep recurrent neural networks identify transgender patients.

Joseph D. Romano, Kenrick Cato, Rami Vanguri, Nicholas P. Tatonetti

Proceedings of the AMIA 2017, 2017

The Use of Informatics to Reduce Disparities in Transgender Health.

Kenrick Cato, Joseph D. Romano, Rami Vanguri, Nicholas P. Tatonetti

Proceedings of the AMIA 2017, 2017