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AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data.

F. Xie, Y. Ning, H. Yuan, B. Goldstein, M. Ong, N. Liu, and B. Chakraborty. CoRR, (2021)

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Sourav Chakraborty

Anirban Chakraborty

Dipanjan Chakraborty

Diptangshu Chakraborty

Martin Chakraborty

Other publications of authors with the same name

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)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)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)Adaptive learning algorithms to optimize mobile applications for behavioral health: guidelines for design decisions.C. Figueroa, A. Aguilera, B. Chakraborty, A. Modiri, J. Aggarwal, N. Deliu, U. Sarkar, J. Williams, and C. Lyles. J. Am. Medical Informatics Assoc., 28 (6): 1225-1234 (2021)Preface to the 1st International Workshop on Algorithmic Behavior Change Support.N. Albers, A. Abdulrahman, D. Richards, C. Figueroa, B. Chakraborty, A. Bhattacharjee, L. He, M. Neerincx, J. Williams, N. Younsi and 4 other author(s). PERSUASIVE (Adjunct), volume 3728 of CEUR Workshop Proceedings, page 1-7. CEUR-WS.org, (2024)AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data.F. Xie, Y. Ning, H. Yuan, B. Goldstein, M. Ong, N. Liu, and B. Chakraborty. CoRR, (2021)AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data.F. Xie, Y. Ning, H. Yuan, B. Goldstein, M. Ong, N. Liu, and B. Chakraborty. J. Biomed. Informatics, (2022)AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data.H. Yuan, F. Xie, M. Ong, Y. Ning, M. Chee, S. Saffari, H. Abdullah, B. Goldstein, B. Chakraborty, and N. Liu. CoRR, (2021)Development and Validation of a Survival Score for the Emergency Department in Singapore.F. Xie, B. Chakraborty, N. Liu, and M. Ong. AMIA, AMIA, (2021)Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques.M. Liu, S. Li, H. Yuan, M. Ong, Y. Ning, F. Xie, S. Saffari, Y. Shang, V. Volovici, B. Chakraborty and 1 other author(s). Artif. Intell. Medicine, (August 2023)

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Disambiguation of "Chakraborty, Bibhas"

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AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data.

Please choose a person to relate this publication to

Sourav Chakraborty

Anirban Chakraborty

Dipanjan Chakraborty

Diptangshu Chakraborty

Martin 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 AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data.

Please choose a person to relate this publication to

Sourav Chakraborty

Anirban Chakraborty

Dipanjan Chakraborty

Diptangshu Chakraborty

Martin 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

AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data.