Digital Determinants of Health: Health data poverty amplifies existing health disparities-A scoping review.
Artificial 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 o...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2023-10-01
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| Series: | PLOS Digital Health |
| Online Access: | https://journals.plos.org/digitalhealth/article/file?id=10.1371/journal.pdig.0000313&type=printable |
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| author | Kenneth Eugene Paik Rachel Hicklen Fred Kaggwa Corinna Victoria Puyat Luis Filipe Nakayama Bradley Ashley Ong Jeremey N I Shropshire Cleva Villanueva |
| author_facet | Kenneth Eugene Paik Rachel Hicklen Fred Kaggwa Corinna Victoria Puyat Luis Filipe Nakayama Bradley Ashley Ong Jeremey N I Shropshire Cleva Villanueva |
| author_sort | Kenneth Eugene Paik |
| collection | DOAJ |
| description | Artificial 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 tools. |
| format | Article |
| id | doaj-art-e51d6d45044045ea847e697fa9598167 |
| institution | Kabale University |
| issn | 2767-3170 |
| language | English |
| publishDate | 2023-10-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLOS Digital Health |
| spelling | doaj-art-e51d6d45044045ea847e697fa95981672025-02-05T05:33:38ZengPublic Library of Science (PLoS)PLOS Digital Health2767-31702023-10-01210e000031310.1371/journal.pdig.0000313Digital Determinants of Health: Health data poverty amplifies existing health disparities-A scoping review.Kenneth Eugene PaikRachel HicklenFred KaggwaCorinna Victoria PuyatLuis Filipe NakayamaBradley Ashley OngJeremey N I ShropshireCleva VillanuevaArtificial 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 tools.https://journals.plos.org/digitalhealth/article/file?id=10.1371/journal.pdig.0000313&type=printable |
| spellingShingle | Kenneth Eugene Paik Rachel Hicklen Fred Kaggwa Corinna Victoria Puyat Luis Filipe Nakayama Bradley Ashley Ong Jeremey N I Shropshire Cleva Villanueva Digital Determinants of Health: Health data poverty amplifies existing health disparities-A scoping review. PLOS Digital Health |
| title | Digital Determinants of Health: Health data poverty amplifies existing health disparities-A scoping review. |
| title_full | Digital Determinants of Health: Health data poverty amplifies existing health disparities-A scoping review. |
| title_fullStr | Digital Determinants of Health: Health data poverty amplifies existing health disparities-A scoping review. |
| title_full_unstemmed | Digital Determinants of Health: Health data poverty amplifies existing health disparities-A scoping review. |
| title_short | Digital Determinants of Health: Health data poverty amplifies existing health disparities-A scoping review. |
| title_sort | digital determinants of health health data poverty amplifies existing health disparities a scoping review |
| url | https://journals.plos.org/digitalhealth/article/file?id=10.1371/journal.pdig.0000313&type=printable |
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