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Federated and distributed learning applications for electronic health records and structured medical data: a scoping review.

S. Li, P. Liu, G. Nascimento, X. Wang, F. Leite, B. Chakraborty, C. Hong, Y. Ning, F. Xie, Z. Teo, D. Ting, H. Haddadi, M. Ong, M. Peres, and N. Liu. J. Am. Medical Informatics Assoc., 30 (12): 2041-2049 (November 2023)

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Sourav Chakraborty

Dipanjan Chakraborty

Anirban Chakraborty

Diptangshu Chakraborty

Asok Chakraborty

Other publications of authors with the same name

Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies.F. Xie, H. Yuan, Y. Ning, M. Ong, M. Feng, W. Hsu, B. Chakraborty, and N. Liu. CoRR, (2021)Shapley variable importance clouds for interpretable machine learning.Y. Ning, M. Ong, B. Chakraborty, B. Goldstein, D. Ting, R. Vaughan, and N. Liu. CoRR, (2021)FedScore: A privacy-preserving framework for federated scoring system development.S. Li, Y. Ning, M. Ong, B. Chakraborty, C. Hong, F. Xie, H. Yuan, M. Liu, D. Buckland, Y. Chen and 1 other author(s). J. Biomed. Informatics, (October 2023)Thompson sampling for zero-inflated count outcomes with an application to the Drink Less mobile health study.X. Liu, N. Deliu, T. Chakraborty, L. Bell, and B. Chakraborty. CoRR, (2023)Estimating the optimal linear combination of predictors using spherically constrained optimization.P. Das, D. De, R. Maiti, M. Kamal, K. Hutcheson, C. Fuller, B. Chakraborty, and C. Peterson. BMC Bioinform., 23-S (3): 436 (2022)Shapley variable importance cloud for interpretable machine learning.Y. Ning, M. Ong, B. Chakraborty, B. Goldstein, D. Ting, R. Vaughan, and N. Liu. Patterns, 3 (4): 100452 (2022)Federated and distributed learning applications for electronic health records and structured medical data: A scoping review.S. Li, P. Liu, G. Nascimento, X. Wang, F. Leite, B. Chakraborty, C. Hong, Y. Ning, F. Xie, Z. Teo and 5 other author(s). CoRR, (2023)Benchmarking Predictive Risk Models for Emergency Departments with Large Public Electronic Health Records.F. Xie, J. Zhou, J. Lee, M. Tan, S. Li, L. Rajnthern, M. Chee, B. Chakraborty, A. Wong, A. Dagan and 3 other author(s). CoRR, (2021)Challenges and opportunities of using reinforcement learning to optimize behavioral health interventions delivered via smartphones.C. Figueroa, A. Aguilera, B. Chakraborty, A. Modiri, J. Aggarwal, N. Deliu, U. Sarkar, J. Williams, and C. Lyles. AMIA, AMIA, (2020)Fairness-Aware Interpretable Modeling (FAIM) for Trustworthy Machine Learning in Healthcare.M. Liu, Y. Ning, Y. Ke, Y. Shang, B. Chakraborty, M. Ong, R. Vaughan, and N. Liu. CoRR, (2024)

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Disambiguation of "Chakraborty, Bibhas"

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Federated and distributed learning applications for electronic health records and structured medical data: a scoping review.

Please choose a person to relate this publication to

Sourav Chakraborty

Dipanjan Chakraborty

Anirban Chakraborty

Diptangshu Chakraborty

Asok Chakraborty

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Chakraborty, Bibhas"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Federated and distributed learning applications for electronic health records and structured medical data: a scoping review.

Please choose a person to relate this publication to

Sourav Chakraborty

Dipanjan Chakraborty

Anirban Chakraborty

Diptangshu Chakraborty

Asok Chakraborty

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Federated and distributed learning applications for electronic health records and structured medical data: a scoping review.