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.
Despite challenges of decision making for unrepresented patients, few laws or policy statements offer solutions. This article offers 5 key things to do.
AMA J Ethics. 2019;21(7):E582-586. doi:
10.1001/amajethics.2019.582.
Maxwell F. Lydiatt and William M. Lydiatt, MD, MBA
Portraiture facilitates learners’ explorations of their own and others’ biases, limitations, and approaches to gathering information from and about a source.
AMA J Ethics. 2020;22(6):E499-504. doi:
10.1001/amajethics.2020.499.
Sofie Layton, MRes, Jo Wray, PhD, Victoria Walsh, PhD, and Giovanni Biglino, PhD
Based on an artist’s, bioengineer’s, and health psychologist’s reflections on pediatric and adult group workshop practice settings, this article suggests 8 dimensions of risk that deserve ethical attention.
AMA J Ethics. 2022;24(7):E638-645. doi:
10.1001/amajethics.2022.638.
Critical race theory tools of evaluating stock characters and counter stories can help clinicians and researchers illuminate experiences of those at the margins.
AMA J Ethics. 2022;24(3):E212-217. doi:
10.1001/amajethics.2022.212.
Osler’s contributions to the philosophy and practice of medicine foreground characteristics of a compassionate caregiver, including imperturbability and equanimity.
AMA J Ethics. 2022;24(12):E1166-1171. doi:
10.1001/amajethics.2022.1166.
Artist and researcher Dr Mark Gilbert joins Ethics Talk to discuss arts-based research: what it is, who it’s for, and why we should pay closer attention to it as a method of clinical inquiry.