Training of machine learning models for recurrence prediction in patients with respiratory pathologies
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http://hdl.handle.net/2183/28957
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- Investigación (FCS) [1293]
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Training of machine learning models for recurrence prediction in patients with respiratory pathologiesFecha
2021-10-13Cita bibliográfica
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.
Resumen
[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.
Palabras clave
Electronic health record (EHR)
Machine learning
Linear discriminant analysis
Quadratic discriminant analysis
K-nearest neighbors
Decision trees
Machine learning
Linear discriminant analysis
Quadratic discriminant analysis
K-nearest neighbors
Decision trees
Descripción
Proceeding paper
Versión del editor
Derechos
Creative Commons Attribution 4.0 International License (CC-BY 4.0)
ISSN
2673-4591
