Proposed Feature Selection Technique for Pattern Detection in Patients with Pneumonia Records

Authors

DOI:

https://doi.org/10.3991/ijoe.v20i07.47647

Keywords:

Clustering, Data mining, Scientific data, Patterns, Pneumonia

Abstract


Pneumonia in Peru is a very serious problem. Its impact in recent years has been aggravated due to the Covid-19 pandemic, generating an increase in infections and deaths without distinguishing the age range, which placed this country on the mortality list due to the pandemic. That is why this research seeks the causes of this problem and evaluates what patterns were detected between the years 2019–2022 in patients with pneumonia in Peru from data set from the Comprehensive Health Insurance (SIS). The data presented values related to age, gender, medication and other significant values to understand the disease. The results of the research were achieved by using the PCA technique where the dimensionality of the data was reduced from 28 to 4 main features (Patient’s year of health care, Age, BMI, Department). Finally, with this processed data set, the K-Means algorithm was used, where it was determined that patients in the 60 to 85 years range are the most affected by J189 pneumonia. In addition, an environmental pattern was found in J189 pneumonia. J128, resulting in a focus on patients on the Peruvian coast in places like Lima or La Libertad.

Author Biographies

Jesus Orlando Gil Jauregui, Universidad Nacional Mayor de San Marcos

Is a software engineering undergraduate student at Universidad Nacional Mayor de San Marcos (UNMSM), Peru. His research interests include data science, machine learning, big data, data mining

Angel Gerardo Carmen Cruzatti

Is a bachelor’s student in software engineering at the National University of San Marcos (UNMSM), Peru. His research interest include machine learning, big data, data mining, and software development

Hugo Villaverde Medrano, Universidad Nacional Mayor de San Marcos

Doctor in Educational Administration, Master in Administration and Computer and Systems Engineer. He works as a Business Intelligence Professional at the Comprehensive Health Insurance (SIS) of Peru. Professor  at the University of Peru. Specialist in Artificial Intelligence, Oracle Database Management System and SQL Server

Cover iJOE – Vol 20, No 07, 2024

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Published

2024-05-06

How to Cite

Gil Jauregui, J. O., Carmen Cruzatti, A. G., Cano Lengua, M. A., & Villaverde Medrano, H. (2024). Proposed Feature Selection Technique for Pattern Detection in Patients with Pneumonia Records. International Journal of Online and Biomedical Engineering (iJOE), 20(07), pp. 69–89. https://doi.org/10.3991/ijoe.v20i07.47647

Issue

Vol. 20 No. 07 (2024)

Section

Papers

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Copyright (c) 2024 MIGUEL ANGEL CANO LENGUA, JESUS GIL JAUREGUI, ANGEL CARMEN CRUZATTI, HUGO VILLAVERDE MEDRANO

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