Lightweight federated learning for STIs/HIV prediction

Lightweight federated learning for STIs/HIV prediction

Abstract This paper presents a solution that prioritises high privacy protection and improves communication throughput for predicting the risk of sexually transmissible infections/human immunodeficiency virus (STIs/HIV). The approach utilised Federated Learning (FL) to construct a model from multipl...

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Bibliographic Details
Main Authors: Thi Phuoc Van Nguyen, Wencheng Yang, Zhaohui Tang, Xiaoyu Xia, Amy B. Mullens, Judith A. Dean, Yan Li
Format: Article
Language:English
Published: Nature Portfolio 2024-03-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-024-56115-0

Internet

https://doi.org/10.1038/s41598-024-56115-0

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