Applying Machine Learning Sampling Techniques to Address Data Imbalance in a Chilean COVID-19 Symptoms and Comorbidities Dataset

Applying Machine Learning Sampling Techniques to Address Data Imbalance in a Chilean COVID-19 Symptoms and Comorbidities Dataset

Reliably detecting COVID-19 is critical for diagnosis and disease control. However, imbalanced data in medical datasets pose significant challenges for machine learning models, leading to bias and poor generalization. The dataset obtained from the EPIVIGILA system and the Chilean Epidemiological Sur...

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Bibliographic Details
Main Authors: Pablo Ormeño-Arriagada, Gastón Márquez, David Araya, Carla Rimassa, Carla Taramasco
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Applied Sciences
Subjects:
machine learning algorithms
COVID-19 diagnosis
imbalanced data
sampling methods
classification metrics
epidemiological dataset
Online Access:https://www.mdpi.com/2076-3417/15/3/1132
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https://www.mdpi.com/2076-3417/15/3/1132

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