Inherent Bias in Artificial Intelligence-Based Decision Support Systems for Healthcare
Open accessAbstract
The objective of this article is to discuss the inherent bias involved with artificial intelligence-based decision support systems for healthcare. In this article, the authors describe some relevant work published in this area. A proposed overview of solutions is also presented. The authors believe that the information presented in this article will enhance the readers’ understanding of this inherent bias and add to the discussion on this topic. Finally, the authors discuss an overview of the need to implement transdisciplinary solutions that can be used to mitigate this bias.
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- Authors
- Gurupur, V., & Wan, T. T. H.
- Affiliations
- University of Central Florida (US)
- Corresponding author
- Gurupur, Varadraj
- Venue
- Medicina
- Publisher
- MDPI AG
- Published
- 2020-03-20
- Volume
- 56
- Issue
- 3
- Pages
- 141
- ISSN
- 1010-660X (ISSN-L)
- 1648-9144
- PMC
- PMC7142873
- OpenAlex
- W3011720571
- Cited by
- 42
- References
- 23
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 12 · 2023: 13 · 2022: 2 · 2021: 5 · 2020: 2
- FWCI
- 1.63
- Type
- journal article
- Language
- en
- Open access
- gold
- dx.doi.org
- Licence
- Locations
- Medicina (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Keywords
- algorithmic bias, artificial intelligence, clinical decision support systems, health care, bias mitigation, algorithmic fairness
- MeSH terms
- Artificial Intelligence, Humans, Bias, Decision Support Systems, Clinical
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