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

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dc.contributor.authorMzurikwao, Deogratias
dc.contributor.authorEdward, Mhamilawa Lwidiko
dc.contributor.authorSimba, Daudi
dc.contributor.authorBalandya, Belinda
dc.contributor.authorAssenga , Evelyne
dc.contributor.authorOkanda, Nyatega Evelyne
dc.contributor.authorZeramula, Jonathan
dc.contributor.authorWibonela, Seif
dc.contributor.authorMzurikwao, Zacharia
dc.contributor.authorSunguya, Bruno
dc.date.accessioned2025-11-07T07:10:38Z
dc.date.available2025-11-07T07:10:38Z
dc.date.issued2025-08-05
dc.descriptionThis Journal Article was published by Tanzania Journal of Health Research in 2025
dc.description.abstractAccurate 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.
dc.description.sponsorshipMbeya university of science and Technology
dc.identifier.issnhttps://dx.doi.org/10.4314/thrb.v26i5.16s
dc.identifier.urihttps://repository.must.ac.tz/handle/123456789/508
dc.language.isoen
dc.publisherTanzania Journal of Health Research
dc.titleArtificial Intelligence in determining optimal questions in assessing social socio-economic status of individuals for routine immunisation services in Tanzania
dc.typeArticle
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