Sudeshna Das

According to our database, Sudeshna Das authored at least 21 papers between 2009 and 2024.

Collaborative distances:

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

2024

Recon-all-clinical: Cortical surface reconstruction and analysis of heterogeneous clinical brain MRI.

Karthik Gopinath, Douglas N. Greve, Colin G. Magdamo, Steven E. Arnold, Sudeshna Das, Oula Puonti, Juan Eugenio Iglesias

CoRR, 2024

Leveraging Pre-trained and Transformer-derived Embeddings from EHRs to Characterize Heterogeneity Across Alzheimer's Disease and Related Dementias.

Matthew West, Colin G. Magdamo, Lily Cheng, Yingnan He, Sudeshna Das

CoRR, 2024

2023

causalCmprsk: An R package for nonparametric and Cox-based estimation of average treatment effects in competing risks data.

Bella Vakulenko-Lagun, Colin G. Magdamo, Marie-Laure Charpignon, Bang Zheng, Mark W. Albers, Sudeshna Das

Comput. Methods Programs Biomed., December, 2023

AI-assisted prediction of differential response to antidepressant classes using electronic health records.

Yi-han Sheu, Colin G. Magdamo, Matthew Miller, Sudeshna Das, Deborah Blacker, Jordan W. Smoller

npj Digit. Medicine, 2023

Classification of neurologic outcomes from medical notes using natural language processing.

Marta B. Fernandes, Navid Valizadeh, Haitham Alabsi, Syed A. Quadri, Ryan A. Tesh, Abigail A. Bucklin, Haoqi Sun, Aayushee Jain, Laura Brenner, Elissa M. Ye, Wendong Ge, Sarah I. Collens, Stacie Lin, Sudeshna Das, Gregory K. Robbins, Sahar Zafar, Shibani S. Mukerji, M. Brandon Westover

Expert Syst. Appl., 2023

Cortical Analysis of Heterogeneous Clinical Brain MRI Scans for Large-Scale Neuroimaging Studies.

Karthik Gopinath, Douglas N. Greve, Sudeshna Das, Steven E. Arnold, Colin G. Magdamo, Juan Eugenio Iglesias

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

2022

Robust machine learning segmentation for large-scale analysis of heterogeneous clinical brain MRI datasets.

Benjamin Billot, Colin G. Magdamo, Steven E. Arnold, Sudeshna Das, Juan Eugenio Iglesias

CoRR, 2022

Multi-confound regression adversarial network for deep learning-based diagnosis on highly heterogenous clinical data.

Matthew Leming, Sudeshna Das, Hyungsoon Im

CoRR, 2022

Robust Segmentation of Brain MRI in the Wild with Hierarchical CNNs and no Retraining.

Benjamin Billot, Colin G. Magdamo, Sean E. Arnold, Sudeshna Das, Juan Eugenio Iglesias

CoRR, 2022

Construction of a confounder-free clinical MRI dataset in the Mass General Brigham system for classification of Alzheimer's disease.

Matthew Leming, Sudeshna Das, Hyungsoon Im

Artif. Intell. Medicine, 2022

Robust Segmentation of Brain MRI in the Wild with Hierarchical CNNs and No Retraining.

Benjamin Billot, Colin G. Magdamo, Steven E. Arnold, Sudeshna Das, Juan Eugenio Iglesias

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

2021

Using Deep Learning to Identify Patients with Cognitive Impairment in Electronic Health Records.

Tanish Tyagi, Colin G. Magdamo, Ayush Noori, Zhaozhi Li, Xiao Liu, Mayuresh Deodhar, Zhuoqiao Hong, Wendong Ge, Elissa M. Ye, Yi-han Sheu, Haitham Alabsi, Laura Brenner, Gregory K. Robbins, Sahar Zafar, Nicole Benson, Lidia M. V. R. Moura, John Hsu, Alberto Serrano-Pozo, Dimitry Prokopenko, Rudolph E. Tanzi, Bradley T. Hyman, Deborah Blacker, Shibani S. Mukerji, M. Brandon Westover, Sudeshna Das

CoRR, 2021

2020

Natural Language Processing to Detect Cognitive Concerns in Electronic Health Records Using Deep Learning.

Zhuoqiao Hong, Colin G. Magdamo, Yi-han Sheu, Prathamesh Mohite, Ayush Noori, Elissa M. Ye, Wendong Ge, Haoqi Sun, Laura Brenner, Gregory K. Robbins, Shibani Mukerji, Sahar Zafar, Nicole Benson, Lidia M. V. R. Moura, John Hsu, Bradley T. Hyman, M. Brandon Westover, Deborah Blacker, Sudeshna Das

CoRR, 2020

2014

Pain Research Forum: application of scientific social media frameworks in neuroscience.

Sudeshna Das, Patricia G. Mccaffrey, Megan Talkington, Neil Andrews, Stephane Corlosquet, Adrian Ivinson, Tim Clark

Frontiers Neuroinformatics, 2014

Semantic Web repositories for genomics data using the eXframe platform.

Emily Merrill, Stephane Corlosquet, Paolo Ciccarese, Tim Clark, Sudeshna Das

J. Biomed. Semant., 2014

Using eXframe to Build Semantic Web Genomics Repositories.

Emily Merrill, Shannan J. Ho Sui, Stephane Corlosquet, Tim Clark, Sudeshna Das

Proceedings of the 7th International Workshop on Semantic Web Applications and Tools for Life Sciences, 2014

2012

Translating standards into practice - One Semantic Web API for Gene Expression.

Helena F. Deus, Eric Prud'hommeaux, Michael Miller, Jun Zhao, James Malone, Tomasz Adamusiak, Jamie P. McCusker, Sudeshna Das, Philippe Rocca-Serra, Ronan Fox, M. Scott Marshall

J. Biomed. Informatics, 2012

2011

eXframe: reusable framework for storage, analysis and visualization of genomics experiments.

Amit U. Sinha, Emily Merrill, Scott A. Armstrong, Timothy W. Clark, Sudeshna Das

BMC Bioinform., 2011

An open annotation ontology for science on web 3.0.

Paolo Ciccarese, Marco Ocana, Leyla Jael García Castro, Sudeshna Das, Tim Clark

J. Biomed. Semant., 2011

2009

Building biomedical web communities using a semantically aware content management system.

Sudeshna Das, Lisa Girard, Tom Green, Louis Weitzman, Alister Lewis-Bowen, Tim Clark

Briefings Bioinform., 2009

Scientific publications on Web 3.0.

Mark Goetz, Tim Clark, Sudeshna Das, Lisa Girard

Proceedings of the Rethinking Electronic Publishing: Innovation in Communication Paradigms and Technologies, 2009