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

Molinero-Rodríguez, AinhoaGuerra-Tort, CarlaSuárez-Ulloa, VictoriaLópez Gestal, José ManuelPereira, JavierAguiar-Pulido, Vanessa2021-11-262021-11-262021-10-13Molinero 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):20.2673-4591http://hdl.handle.net/2183/28957Proceeding paper[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.engCreative Commons Attribution 4.0 International License (CC-BY 4.0)http://creativecommons.org/licenses/by/4.0/Electronic health record (EHR)Machine learningLinear discriminant analysisQuadratic discriminant analysisK-nearest neighborsDecision treesTraining of machine learning models for recurrence prediction in patients with respiratory pathologiesconference outputopen access10.3390/engproc2021007020