Algorithmic Bias from the Perspectives of Healthcare Professionals

Jennifer Xu, Tamara Babaian

2025

Abstract

This paper focuses on algorithmic bias of machine learning and artificial intelligence applications in healthcare information systems. Based on the quantitative data and qualitative comments from a survey and interviews with healthcare professionals, who have different job roles (e.g., clinical vs. administrative), this study provides findings about the relationships between algorithmic bias, perceived fairness, and the intended acceptance and adoption of ML algorithms and algorithm generated outcomes. The results suggest that the opinions of healthcare professionals toward the causes of algorithmic bias, the criteria of algorithm assessment, the perceived fairness, and bias mitigation approaches may vary depending on their job roles, perspectives, tasks, and the algorithm characteristics. More research is needed to investigate algorithmic bias to ensure fairness and equality in healthcare.

Paper Citation

in Harvard Style

Xu J. and Babaian T. (2025). Algorithmic Bias from the Perspectives of Healthcare Professionals. In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF; ISBN 978-989-758-731-3, SciTePress, pages 17-28. DOI: 10.5220/0013076500003911

in Bibtex Style

@conference{healthinf25,
author={Jennifer Xu and Tamara Babaian},
title={Algorithmic Bias from the Perspectives of Healthcare Professionals},
booktitle={Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF},
year={2025},
pages={17-28},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013076500003911},
isbn={978-989-758-731-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF
TI - Algorithmic Bias from the Perspectives of Healthcare Professionals
SN - 978-989-758-731-3
AU - Xu J.
AU - Babaian T.
PY - 2025
SP - 17
EP - 28
DO - 10.5220/0013076500003911
PB - SciTePress