Regresión logística: un ejemplo para la predicción de infartos

Translated title of the contribution: Logistic regression: an example for infarct prediction

Henry Silva-Marchan, Gerardo Ortiz-Castro, Oscar Jhan Marcos Peña-Cáceres, Manuel Alejandro More-More

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Technological advances have allowed the development and availability of specialized tools for the use of historical data. In many cases, these tools are used for decision-making in multidisciplinary institutions that require support for the development of their activities, particularly in the health sector. The purpose of this study is to use a machine learning algorithm to predict heart attacks using demographic and family health data. The methodology focused on the extraction of open data from the Demographic and Family Health Survey (ENDES) applied in 2021 in Peru, characterization and execution of machine learning techniques using Orange Data Mining software. In this first approach, the results show that the logistic regression model has an accuracy of 0.99% on the prediction of heart attacks under the use of ENDES Peru 2021 data. For future studies, it is suggested to incorporate unstructured data such as text documents, sensor data and images to strengthen the reliability of the model.

Translated title of the contributionLogistic regression: an example for infarct prediction
Original languageSpanish
Title of host publicationProceedings of the 21st LACCEI International Multi-Conference for Engineering, Education and Technology
Subtitle of host publicationLeadership in Education and Innovation in Engineering in the Framework of Global Transformations: Integration and Alliances for Integral Development, LACCEI 2023
EditorsMaria M. Larrondo Petrie, Jose Texier, Rodolfo Andres Rivas Matta
PublisherLatin American and Caribbean Consortium of Engineering Institutions
ISBN (Electronic)9786289520743
StatePublished - 2023
Event21st LACCEI International Multi-Conference for Engineering, Education and Technology, LACCEI 2023 - Buenos Aires, Argentina
Duration: 19 Jul 202321 Jul 2023

Publication series

NameProceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Volume2023-July
ISSN (Electronic)2414-6390

Conference

Conference21st LACCEI International Multi-Conference for Engineering, Education and Technology, LACCEI 2023
Country/TerritoryArgentina
CityBuenos Aires
Period19/07/2321/07/23

Bibliographical note

Publisher Copyright:
© 2023 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.

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