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Training of machine learning models for recurrence prediction in patients with respiratory pathologies

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http://hdl.handle.net/2183/28957
Creative Commons Attribution 4.0 International License (CC-BY 4.0)
Except where otherwise noted, this item's license is described as Creative Commons Attribution 4.0 International License (CC-BY 4.0)
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Title
Training of machine learning models for recurrence prediction in patients with respiratory pathologies
Author(s)
Molinero-Rodríguez, Ainhoa
Guerra Tort, Carla
Suárez-Ulloa, Victoria
López Gestal, José Manuel
Pereira-Loureiro, Javier
Aguiar-Pulido, Vanessa
Date
2021-10-13
Citation
Molinero Rodríguez A, Guerra Tor C, Suárez Ulloa V, López Gestal JM, Pereira J, Aguiar Pulido V. Training of machine learning models for recurrence prediction in patients with respiratory pathologies. Eng Proc. 2021;7(1):20.
Abstract
[Abstract] Information extracted from electronic health records (EHRs) is used for predictive tasks and clinical pattern recognition. Machine learning techniques also allow the extraction of knowledge from EHR. This study is a continuation of previous work in which EHRs were exploited to make predictions about patients with respiratory diseases. In this study, we will try to predict the recurrence of patients with respiratory diseases using four different machine learning algorithms.
Keywords
Electronic health record (EHR)
Machine learning
Linear discriminant analysis
Quadratic discriminant analysis
K-nearest neighbors
Decision trees
 
Description
Proceeding paper
Editor version
https://doi.org/10.3390/engproc2021007020
Rights
Creative Commons Attribution 4.0 International License (CC-BY 4.0)
ISSN
2673-4591

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