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...

Full description

Saved in:
Bibliographic Details
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
Tags: Add Tag
No Tags, Be the first to tag this record!
Login for hold and recall information

Internet

http://journals.lww.com/10.1097/AS9.0000000000000573

Similar Items