The American journal of bioethics : AJOB
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The genome between socially constructed racial groups is 99.5%-99.9% identical; the 0.1%-0.5% variation between any two unrelated individuals is greatest between individuals in the same racial group; and there are no identifiable racial genomic clusters. Nevertheless, race continues to be used as a biological reality in health disparities research, medical guidelines, and standards of care reinforcing the notion that racial and ethnic minorities are inferior, while ignoring the health problems of Whites. This article discusses how the continued misuse of race in medicine and the identification of Whites as the control group, which reinforces this racial hierarchy, are examples of racism in medicine that harm all us. To address this problem, race should only be used as a factor in medicine when explicitly connected to racism or to fulfill diversity and inclusion efforts.
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Along with potential benefits to healthcare delivery, machine learning healthcare applications (ML-HCAs) raise a number of ethical concerns. Ethical evaluations of ML-HCAs will need to structure the overall problem of evaluating these technologies, especially for a diverse group of stakeholders. ⋯ Over this model, we layer key questions that raise value-based issues, along with ethical considerations identified in large part by a literature review, but also identifying some ethical considerations that have yet to receive attention. This pipeline model framework will be useful for systematic ethical appraisals of ML-HCA from development through implementation, and for interdisciplinary collaboration of diverse stakeholders that will be required to understand and subsequently manage the ethical implications of ML-HCAs.