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Training of machine learning models for recurrence prediction in patients with respiratory pathologies
| dc.contributor.author | Molinero-Rodríguez, Ainhoa | |
| dc.contributor.author | Guerra Tort, Carla | |
| dc.contributor.author | Suárez Ulloa, Victoria | |
| dc.contributor.author | López Gestal, José Manuel | |
| dc.contributor.author | Pereira-Loureiro, Javier | |
| dc.contributor.author | Aguiar-Pulido, Vanessa | |
| dc.date.accessioned | 2021-11-26T10:37:09Z | |
| dc.date.available | 2021-11-26T10:37:09Z | |
| dc.date.issued | 2021-10-13 | |
| dc.identifier.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. | es_ES |
| dc.identifier.issn | 2673-4591 | |
| dc.identifier.uri | http://hdl.handle.net/2183/28957 | |
| dc.description | Proceeding paper | es_ES |
| dc.description.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. | es_ES |
| dc.description.sponsorship | Centro de Investigación de Galicia CITIC and Campus Innova (agreement I+D+ 2019-20) is funded by Consellería de Educación, Universidade e Formación Profesional from Xunta de Galicia and European Union (European Regional Development Fund - FEDER Galicia 2014-2020 Program) by grant ED431G 2019/01 and Universidade da Coruña. Partially supported by the Spanish Ministry of Science (Challenges of Society 2019) PID2019-104323RB-C33 | |
| dc.description.sponsorship | Xunta de Galicia; ED431G 2019/01 | |
| dc.language.iso | eng | es_ES |
| dc.publisher | MDPI | es_ES |
| dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-104323RB-C33/ES/EVALUACION Y ASESORAMIENTO PARA LA MEJOR EFICIENCIA Y EFECTIVIDAD DE LA TECNOLOGIA DE APOYO/ | |
| dc.relation.uri | https://doi.org/10.3390/engproc2021007020 | es_ES |
| dc.rights | Creative Commons Attribution 4.0 International License (CC-BY 4.0) | es_ES |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
| dc.subject | Electronic health record (EHR) | es_ES |
| dc.subject | Machine learning | es_ES |
| dc.subject | Linear discriminant analysis | es_ES |
| dc.subject | Quadratic discriminant analysis | es_ES |
| dc.subject | K-nearest neighbors | es_ES |
| dc.subject | Decision trees | es_ES |
| dc.title | Training of machine learning models for recurrence prediction in patients with respiratory pathologies | es_ES |
| dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
| dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
| UDC.journalTitle | Engineering Proceedings | es_ES |
| UDC.volume | 7 | es_ES |
| dc.identifier.doi | 10.3390/engproc2021007020 | |
| UDC.conferenceTitle | IV Congreso XoveTIC 2021 | es_ES |
