Determinants predicting HIV testing among Filipino women using machine learning models with SMOTE preprocessing

Determinants predicting HIV testing among Filipino women using machine learning models with SMOTE preprocessing

Women face a greater risk of contracting HIV due to their anatomy and the impacts of gender inequality. Despite this, only 8% of Filipino women have ever tested for HIV, according to the results of the 2022 National Demographic Health Survey. This study aimed to identify the determinants of HIV test...

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Bibliographic Details
Main Authors: Arriola, Andrei Joseph, Salting, Francesca Marie Orolfo
Format: text
Language:English
Published: Animo Repository 2024
Subjects:
HIV (Viruses)—Testing
Women—Health and hygiene > Philippines
Logistic regression analysis
Mathematics
Public Health
Online Access:https://animorepository.dlsu.edu.ph/etdb_math/39
https://animorepository.dlsu.edu.ph/context/etdb_math/article/1042/viewcontent/2024_Arriola_Salting_Determinants_predicting_HIV_testing_among_Filipino_women_using_ma.pdf
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Institution: De La Salle University
Language: English

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https://animorepository.dlsu.edu.ph/etdb_math/39
https://animorepository.dlsu.edu.ph/context/etdb_math/article/1042/viewcontent/2024_Arriola_Salting_Determinants_predicting_HIV_testing_among_Filipino_women_using_ma.pdf

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