Ai bias in healthcare: Using impactpro as a case study for healthcare practitioners' duties to engage in anti-bias measures

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Abstract

The introduction of ImpactPro to identify patients with complex health needs suggests that current bias and impacts of bias in healthcare AIs stem from historically biased practices leading to biased datasets, a lack of oversight, as well as bias in practitioners who are overseeing AIs. In order to improve these outcomes, healthcare practitioners need to engage in current best practices for anti-bias training.

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APA

Sargent, S. L. (2021). Ai bias in healthcare: Using impactpro as a case study for healthcare practitioners’ duties to engage in anti-bias measures. Canadian Journal of Bioethics. University of Montreal. https://doi.org/10.7202/1077639AR

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