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Review
. 2020 Mar 20;56(3):141.
doi: 10.3390/medicina56030141.

Inherent Bias in Artificial Intelligence-Based Decision Support Systems for Healthcare

Varadraj Gurupur  1 , Thomas T H Wan  1
Affiliations
Review

Inherent Bias in Artificial Intelligence-Based Decision Support Systems for Healthcare

Varadraj Gurupur et al. Medicina (Kaunas). .

Abstract

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.

Keywords: artificial intelligence; decision support systems; healthcare information systems; knowledge bias; knowledge-based systems.

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Conflict of interest statement

The authors declare no conflict of interest.

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References

    1. Challen R., Denny J., Pitt M., Gompels L., Edwards T., Tsaneva-Atanasova K. Artificial intelligence, bias and clinical safety. BMJ Qual. Saf. 2019;28:231–237. doi: 10.1136/bmjqs-2018-008370. - DOI - PMC - PubMed
    1. Althubaiti A. Information bias in health research: Definition, pitfalls, and adjustment methods. J. Multidiscip. Res. Healthc. 2016;9:211. doi: 10.2147/JMDH.S104807. - DOI - PMC - PubMed
    1. Gurupur V., Kulkarni S.A., Liu X., Desai U., Nasir A. Analysing the power of deep learning techniques over the traditional methods using medicare utilization and provider data. J. Exp. Theor. Artif. Intell. 2019;31:99–115. doi: 10.1080/0952813X.2018.1518999. - DOI
    1. Holman L., Head M.L., Lanfear R., Jennions M. Evidence of experimental bias in the life sciences: Why we need blind data recording. PLoS ONE. 2015;13:e1002190. doi: 10.1371/journal.pbio.1002190. - DOI - PMC - PubMed
    1. Henriksen K., Kaplan H. Hindsight bias, outcome knowledge and adaptive learning. Qual. Saf. Healthc. 2003;12:ii46–ii50. doi: 10.1136/qhc.12.suppl_2.ii46. - DOI - PMC - PubMed

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