Federated Learning for Predicting Major Postoperative Complications

Federated Learning for Predicting Major Postoperative Complications

Objective:. To develop a robust model to accurately predict the risk of postoperative complications using clinical data from multiple institutions while ensuring data privacy. Background:. Building accurate, artificial intelligence models to predict postoperative complications relies on accessibilit...

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Main Authors: Yuanfang Ren, PhD, Yonggi Park, PhD, Benjamin Shickel, PhD, Ziyuan Guan, MS, Ayush Patel, Yingbo Ma, PhD, Zhenhong Hu, PhD, Jeremy A. Balch, MD, Tyler J. Loftus, MD, PhD, Parisa Rashidi, PhD, Tezcan Ozrazgat-Baslanti, PhD, Azra Bihorac, MD, MS
Format: Article
Language:English
Published: Wolters Kluwer Health 2025-06-01
Series:Annals of Surgery Open
Online Access:http://journals.lww.com/10.1097/AS9.0000000000000573
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http://journals.lww.com/10.1097/AS9.0000000000000573

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