… or standards to address algorithmic bias in healthcare; a gap … of algorithmic bias that may
perpetuate health inequities. We … of bias, in AI, describing how it plays out in the healthcare …

… The data inequities that generate algorithmic bias are the same as those that determine who
… algorithmic bias in health systems, a risk inherent in AI, explore its implications for health …

… view bias as a contributing factor to health inequities, which can be exacerbated by disparities
in health care access, allocation, and outcomes. Increasing use of clinical algorithms has …

… algorithmic fairness and algorithmic bias. Fairness concerns apply specifically when algorithms
… event on the one hand and unfair prejudice leading to inequity on the other (akin to what …

… Conclusions and Relevance Multiple stakeholders must partner to create systems, processes,
regulations, incentives, standards, and policies to mitigate and prevent algorithmic bias. …

… ensure patients' health equity. In this study,we reviewed the causes and coping strategies
related to algorithmic bias in healthcare,with the aim of improving healthcare providers' …

… We identified a relative wealth of publications covering algorithmic bias, but in terms of
original research, very few publications discussed the wider impact of AI on patient care and the …

… racial and ethnic bias in algorithms associated with health inequities, often emphasizing the
… -standing inequities. The widespread and increasing use of algorithms in health care and …

… risk (63, 71), and lung cancer eligibility (83), the statistical methods used for model calibration
were modified with innovative techniques designed to mitigate potential algorithmic bias. …

… interventions and highlight large structural barriers that affect health inequalities. … Algorithmic
fairness could be necessary to fix statistical limitations reflective of perniciously biased data, …