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

• المؤلفون الرئيسيون: Arriola, Andrei Joseph, Salting, Francesca Marie Orolfo
• التنسيق: text
• اللغة: English
• منشور في: Animo Repository 2024
• الموضوعات: HIV (Viruses)—Testing; Women—Health and hygiene > Philippines; Logistic regression analysis; Mathematics; Public Health
• الوصول للمادة أونلاين: 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

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...