Optimization of Tree-Based Machine Learning Models to Predict the Length of Hospital Stay Using Genetic Algorithm
Published 2023 View Full Article
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Title
Optimization of Tree-Based Machine Learning Models to Predict the Length of Hospital Stay Using Genetic Algorithm
Authors
Keywords
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Journal
Journal of Healthcare Engineering
Volume 2023, Issue -, Pages 1-14
Publisher
Hindawi Limited
Online
2023-02-15
DOI
10.1155/2023/9673395
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- (2018) Katherine Meadows et al. JOURNAL OF CARDIOTHORACIC AND VASCULAR ANESTHESIA
- OUP accepted manuscript
- (2018) NEUROSURGERY
- Analysis of length of hospital stay using electronic health records: A statistical and data mining approach
- (2018) Hyunyoung Baek et al. PLoS One
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