Henderson, Alexis
(2023)
The Potential Impact of Artificial Intelligence on Health Disparities in Dermatology: A Literature Review.
Master Essay, University of Pittsburgh.
Abstract
As is the case with many health outcomes, minoritized groups have worse morbidity and mortality rates in a variety of skin conditions compared to their White counterparts. As the field of medicine continues to develop, innovative technology such as the introduction of artificial intelligence into clinical practice is a not-so-distant reality. This is especially the case with specialties dependent on pattern recognition such as dermatology. Since this an emerging sector of medicine, it is important to evaluate the state of current literature on this topic to understand its future impacts on skin health equity. An Ovid-Medline literature search, a hand search using SciWheel-recommended articles, and a Google Scholar hand search yielded 10 articles discussing the health equity impact of using artificial intelligence as a dermatological diagnostic tool among diverse patient populations. While included studies have limitations that make their results difficult to generalize, most included articles demonstrated equally high performances of artificial intelligence models on a wide range of skin colors. All articles pointed towards the necessity of intentionally correcting for biases in the development, training, validation, and testing of artificial intelligence algorithms and models. Current literature in this area primarily focuses on optimizing accuracy, rather than promoting health equity. Future studies in this area including diverse patient populations are needed to determine the most equitable methods of preparing artificial intelligence diagnostic tools for widespread clinical practice, thereby avoiding future health inequities and a broader public health issue.
Share
| Citation/Export: |
|
| Social Networking: |
|
Details
| Item Type: |
Other Thesis, Dissertation, or Long Paper
(Master Essay)
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| Contributors: |
| Contribution | Contributors Name | Email | Pitt Username | ORCID  |
|---|
| Committee Chair | Hill, Ashley | avh16@pitt.edu | avh16 | UNSPECIFIED | | Committee Member | James, Alaina | jamesaj@upmc.edu | UNSPECIFIED | UNSPECIFIED | | Committee Member | Brown-Podgorski, Brittany | brittany.brownpodgorski@pitt.edu | brittany.brownpodgorski | UNSPECIFIED |
|
| Date: |
5 January 2023 |
| Date Type: |
Completion |
| Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
| Number of Pages: |
78 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
School of Public Health > Epidemiology |
| Degree: |
MPH - Master of Public Health |
| Thesis Type: |
Master Essay |
| Refereed: |
Yes |
| Date Deposited: |
05 Jan 2023 14:28 |
| Last Modified: |
05 Jan 2023 14:28 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/44038 |
Metrics
Monthly Views for the past 3 years
Plum Analytics
Actions (login required)
 |
View Item |
![[img]](https://d-scholarship.pitt.edu/style/images/fileicons/application_pdf.png)
![[feed]](/images/feed-icon-32x32.png){kind=icon}