Camillo Lamanna, MMathPhil, MBBS and Lauren Byrne, MBBS
Perhaps machine learning systems trained on patients’ electronic health records and social media footprints could be used as decision aids when patients lack capacity or face overwhelming decisions.
AMA J Ethics. 2018;20(9):E902-910. doi:
10.1001/amajethics.2018.902.
Elizabeth Boskey, PhD, MPH, MSSW, Amir Taghinia, MD, and Oren Ganor, MD
Training should be implemented to respond to clinical staff members’ concerns about trans patients occupying sex-segregated spaces and to help mitigate anti-trans bias.
AMA J Ethics. 2018;20(11):E1067-1074. doi:
10.1001/amajethics.2018.1067.
With a focus on health justice, literature review suggests possible relationships between HPV type and geography and demonstrates that insurance status matters.
AMA J Ethics. 2019;21(3):E269-272. doi:
10.1001/amajethics.2019.269.
Hannah R. Sullivan and Scott J. Schweikart, JD, MBE
Legal questions regarding clinicians’ and technology manufacturers’ liability arise when algorithmic recommendations generated by the technology are hard to understand.
AMA J Ethics. 2019;21(2):E160-166. doi:
10.1001/amajethics.2019.160.
One recent essay suggests that emphasis on social justice in medical education is done at the expense of clinicians’ technical competency. This is a response to that stance.
AMA J Ethics. 2020;22(3):E253-254. doi:
10.1001/amajethics.2020.253.