Vidul A. Panickan on Muck Rack

Vidul A. Panickan

As seen in: Nature, Gastrointestinal Endoscopy
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Articles

Tu1495 MACHINE-LEARNING BASED STRATIFICATION IDENTIFIES TREATMENT TRAJECTORY SUBTYPES AND UNMET NEED IN INFLAMMATORY BOWEL DISEASES

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By Sara Sweet, Joshua Brown, Marie Sanchirico, Xin Xiong, Enci Cai, Vidul A. Panickan, Wasuwit Wanchaitanawong, Rui Duan, Chiahung Chou, Joshua E. Brown, Georgina A Hughes, Tianxi Cai, Ashwin N Ananthakrishnan
| Gastrointestinal Endoscopy Verified
Also available on ScienceDirect
Open in Who Shared Issue with article?

Representation learning to advance multi-institutional studies with electronic health record data from US and France

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By Doudou Zhou, Linshanshan Wang, Suqi Liu, Xin Xiong, Griffier Romain, Boris P Hejblum, Yun-Chung Liu, Chuan Hong, Clara-Lea Bonzel, Tianrun Cai, Kevin Pan, Yuk-Lam Ho, LAUREN COSTA, J. Michael Gaziano, Kenneth D. Mandl, Vianney Jouhet, Rodolphe Thiébaut, Zongqi Xia, Kelly Kasulis Cho, Katherine P Liao, Tianxi Cai, Ziming Gan, Vidul A. Panickan
| Nature Verified
Abstract The widespread adoption of electronic health records has created new opportunities for translational clinical research, yet this promise remains constrained by fragmented data across privacy-siloed institutions and substantial heterogeneity in local coding practices. While privacy-preserving collaborative learning allows institutions to work together without sharing patient-level data, it does not address inconsistencies in how clinical concepts are represented across sites.
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