A novel interpretative tool for early prediction of low cardiac output syndrome after valve surgery: online machine learning models

A novel interpretative tool for early prediction of low cardiac output syndrome after valve surgery: online machine learning models

AbstractObjective Low cardiac output syndrome (LCOS) is a severe complication after valve surgery, with no uniform standard for early identification. We developed interpretative machine learning (ML) models for predicting LCOS risk preoperatively and 0.5 h postoperatively for intervention in advance...

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Bibliographic Details
Main Authors: Liang Hong, Tianling Feng, Runze Qiu, Shiteng Lin, Yinying Xue, Kaizong Huang, Chen Chen, Jiawen Wang, Rongrong Xie, Sanbing Song, Cui Zhang, Jianjun Zou
Format: Article
Language:English
Published: Taylor & Francis Group 2023-12-01
Series:Annals of Medicine
Subjects:
Low cardiac output syndrome
valve surgery
machine learning
prediction
interpretative
online
Online Access:https://www.tandfonline.com/doi/10.1080/07853890.2023.2293244

Internet

https://www.tandfonline.com/doi/10.1080/07853890.2023.2293244

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