FedPseudo: Privacy-Preserving Pseudo Value-Based Deep Learning Models for Federated Survival Analysis-Reference-Cited by-同舟云学术

FedPseudo: Privacy-Preserving Pseudo Value-Based Deep Learning Models for Federated Survival Analysis

Published:2023-08-04 Issue: Volume: Page:
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Container-title:Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Rahman Md Mahmudur¹^ORCID,Purushotham Sanjay¹^ORCID

Affiliation:

1. University of Maryland, Baltimore County, Baltimore, MD, USA

Funder

NSF (National Science Foundation)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3580305.3599348

Reference50 articles.

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3. Mathieu Andreux , Andre Manoel , Romuald Menuet , Charlie Saillard , and Chloé Simpson . 2020. Federated survival analysis with discrete-time Cox models. arXiv preprint arXiv:2006.08997 ( 2020 ). Mathieu Andreux, Andre Manoel, Romuald Menuet, Charlie Saillard, and Chloé Simpson. 2020. Federated survival analysis with discrete-time Cox models. arXiv preprint arXiv:2006.08997 (2020).

4. Laura Antolini , Patrizia Boracchi , and Elia Biganzoli . 2005. A time-dependent discrimination index for survival data. Statistics in medicine , Vol. 24 , 24 ( 2005 ), 3927--3944. Laura Antolini, Patrizia Boracchi, and Elia Biganzoli. 2005. A time-dependent discrimination index for survival data. Statistics in medicine, Vol. 24, 24 (2005), 3927--3944.

5. Alberto Archetti and Matteo Matteucci . 2023. Federated Survival Forests. arXiv preprint arXiv:2302.02807 ( 2023 ). Alberto Archetti and Matteo Matteucci. 2023. Federated Survival Forests. arXiv preprint arXiv:2302.02807 (2023).

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