Development of an ensemble prediction model for acute graft-versus-host disease in allogeneic transplantation based on machine learning

Development of an ensemble prediction model for acute graft-versus-host disease in allogeneic transplantation based on machine learning

Abstract Background Acute graft-versus-host disease (aGVHD) is a major post-transplantation complication and one of the most significant causes of non-relapse-related death. However, the massive and complex clinical data make aGVHD difficult to predict. Machine learning (ML), a branch of artificial...

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Bibliographic Details
Main Authors: Lin Song, Xingwei Wu, Mengjia Xu, Ling Xue, Xun Yu, Zongqi Cheng, Chenrong Huang, Liyan Miao
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Acute graft-versus-host disease
Prediction model
Ensemble model
Machine learning
Allogeneic haematopoietic stem cell transplantation
Online Access:https://doi.org/10.1186/s12911-025-03059-8
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