Artificial Intelligence in determining optimal questions in assessing social socio-economic status of individuals for routine immunisation services in Tanzania

Abstract
Accurate determination of socio-economic status (SES) is crucial for equitable access to immunization services. Existing SES assessment tools, like the DHS wealth index, are comprehensive but impractical for routine clinical settings due to their length. Objective: To identify the minimum number of questions that can validly determine SES using artificial intelligence (AI), and to assess their validity compared to the standard DHS wealth index. Methods: This study applied Principal Component Analysis (PCA), Convolutional Neural Networks (CNN), and Artificial Neural Networks (ANN) using the DHS wealth index as the gold standard. Data were collected from routine RCH clinics in Tanzania. CNN was used to extract weights for each question, and ANN was trained to validate different subsets of questions.
Description
This Journal Article was published by Tanzania Journal of Health Research in 2025
Keywords
Citation