How does the accuracy of deep neural network models trained to classify clinical images of
skin conditions vary across skin color? While recent studies demonstrate computer vision …

Although advances in deep learning systems for image-based medical diagnosis
demonstrate their potential to augment clinical decision-making, the effectiveness of …

Deep neural networks have proven to be highly effective in efficiently handling various
medical tasks, including classification and segmentation in the healthcare domain …

Non-attendance to dermatology outpatient appointments is a risk factor for poorer patient
outcomes. The culturally and linguistically diverse (CALD) communities in Australia have …

Another demonstration of allyship is the affinity group model implemented within many
schools of medicine and business organizations. An example of this process in action can …

journal homepage: minority groups. Each event has served as an avenue to teach students
about the necessary components for a strong dermatological residency application …

VOL. 108 NO. 1 I JULY 2021 21 WWW. MDEDGE. COM/DERMATOLOGY respondents
reported that non–skin of color clinic dermatologists examined their hair with the end of a …

Abstract Background/Objectives There is limited literature focussing on the demographics of
patients presenting to public dermatology outpatient clinics, with an even smaller amount …

While artificial intelligence (AI) appears to be surpassing the performance of human experts
on a wide variety of games and real-world tasks, these algorithms are prone to systematic …

The use of automated machine learning-based skin lesion diagnosis systems has a huge
potential to not only speed up the diagnosis process for deadly skin conditions such …