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dc.contributor.authorPaik, Kenneth Eugene
dc.contributor.authorHicklen, Rachel
dc.contributor.authorKaggwa, Fred
dc.contributor.authorPuyat, Corinna Victoria
dc.contributor.authorNakayama, Luis Filipe
dc.contributor.authorOng, Bradley Ashley
dc.contributor.authorShropshire, Jeremey N. I.
dc.contributor.authorVillanueva, Cleva
dc.date.accessioned2024-01-05T12:30:19Z
dc.date.available2024-01-05T12:30:19Z
dc.date.issued2023
dc.identifier.citationPaik, K. E., Hicklen, R., Kaggwa, F., Puyat, C. V., Nakayama, L. F., Ong, B. A., ... & Villanueva, C. (2023). Digital Determinants of Health: Health data poverty amplifies existing health disparities—A scoping review. PLOS Digital Health, 2(10), e0000313.en_US
dc.identifier.urihttp://ir.must.ac.ug/xmlui/handle/123456789/3323
dc.description.abstractArtificial intelligence (AI) and machine learning (ML) have an immense potential to transform healthcare as already demonstrated in various medical specialties. This scoping review focuses on the factors that influence health data poverty, by conducting a literature review, analysis, and appraisal of results. Health data poverty is often an unseen factor which leads to perpetuating or exacerbating health disparities. Improvements or failures in addressing health data poverty will directly impact the effectiveness of AI/ML systems. The potential causes are complex and may enter anywhere along the development process. The initial results highlighted studies with common themes of health disparities (72%), AL/ML bias (28%) and biases in input data (18%). To properly evaluate disparities that exist we recommend a strengthened effort to generate unbiased equitable data, improved understanding of the limitations of AI/ML tools, and rigorous regulation with continuous monitoring of the clinical outcomes of deployed toolsen_US
dc.language.isoen_USen_US
dc.publisherPLOS Digital Healthen_US
dc.subjectArtificial intelligenceen_US
dc.subjectMachine learningen_US
dc.subjectHealthcareen_US
dc.titleDigital Determinants of Health: Health data poverty amplifies existing health disparities— A scoping reviewen_US
dc.typeArticleen_US


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