Predicting hospital outpatient volume using XGBoost: a machine learning approach

Predicting hospital outpatient volume using XGBoost: a machine learning approach

Abstract Hospital outpatient volume is influenced by a variety of factors, including environmental conditions and healthcare resource availability. Accurate prediction of outpatient demand can significantly enhance operational efficiency and optimize the allocation of medical resources. This study a...

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Bibliographic Details
Main Authors: Lingling Zhou, Qin Zhu, Qian Chen, Ping Wang, Hao Huang
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
XGBoost
Outpatient volume
Machine learning
Climate data
Hospital resource planning
Predictive analytics
Online Access:https://doi.org/10.1038/s41598-025-01265-y
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https://doi.org/10.1038/s41598-025-01265-y

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