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Sudeshna Das

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Massachusetts General Hospital, Boston, MA

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

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Mar 30, 2024
Matthew West, Colin Magdamo, Lily Cheng, Yingnan He, Sudeshna Das

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Cortical analysis of heterogeneous clinical brain MRI scans for large-scale neuroimaging studies

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May 02, 2023
Karthik Gopinath, Douglas N. Greve, Sudeshna Das, Steve Arnold, Colin Magdamo, Juan Eugenio Iglesias

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

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Sep 05, 2022
Benjamin Billot, Colin Magdamo, Steven E. Arnold, Sudeshna Das, Juan. E. Iglesias

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

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May 05, 2022
Matthew Leming, Sudeshna Das, Hyungsoon Im

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

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Mar 07, 2022
Benjamin Billot, Magdamo Colin, Sean E. Arnold, Sudeshna Das, Juan. E. Iglesias

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

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Nov 13, 2021
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 Moura, John Hsu, Alberto Serrano-Pozo, Dimitry Prokopenko, Rudolph E. Tanzi, Bradley T. Hyman, Deborah Blacker, Shibani S. Mukerji, M. Brandon Westover, Sudeshna Das

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

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Nov 12, 2020
Zhuoqiao Hong, Colin G. Magdamo, Yi-han Sheu, Prathamesh Mohite, Ayush Noori, Elissa M. Ye, Wendong Ge, Haoqi Sun, Laura Brenner, Gregory Robbins, Shibani Mukerji, Sahar Zafar, Nicole Benson, Lidia Moura, John Hsu, Bradley T. Hyman, Michael B. Westover, Deborah Blacker, Sudeshna Das

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