Text-to-image generative AI models such as Stable Diffusion are used daily by millions worldwide. However, the extent to which these models exhibit racial and gender stereotypes is not yet fully understood. Here, we document significant biases in Sta...
A growing minority of those with disabilities are people of color (POC), with, for example, autism diagnosis rates now higher for children of color than for white children in the USA. This trend underscores the need for assistive technologies, especi...
Observational health research often relies on accurate and complete race and ethnicity (RE) patient information, such as characterizing cohorts, assessing quality/performance metrics of hospitals and health systems, and identifying health disparities...
BACKGROUND: Artificial intelligence (AI)-based models are increasingly being integrated into cardiovascular medicine. Despite promising potential, racial and ethnic biases remain a key concern regarding the development and implementation of AI models...
Forensic science international. Genetics
Nov 29, 2024
The aim of this study was to test the validity of a predictive model of ancestry affiliation based on Short Tandem Repeat (STR) profiles. Frequencies of 29 genetic markers from the Promega website for four distinct population groups (African American...
BACKGROUND: Integrating artificial intelligence (AI) into intensive care practices can enhance patient care by providing real-time predictions and aiding clinical decisions. However, biases in AI models can undermine diversity, equity, and inclusion ...
BACKGROUND: Despite decades of pursuing health equity, racial and ethnic disparities persist in healthcare in America. For cancer specifically, one of the leading observed disparities is worse mortality among non-Hispanic Black patients compared to n...
Early detection of Alzheimer's disease (AD) is crucial to maximize clinical outcomes. Most disease progression analyses include people with diagnoses of cognitive impairment, limiting understanding of AD risk among those with normal cognition. The ob...
BACKGROUND: While predictive capabilities of machine learning (ML) algorithms for hip and knee total joint arthroplasty (TJA) have been demonstrated in previous studies, their performance in racial and ethnic minority patients has not been investigat...
BACKGROUND: Prior studies characterizing worsening heart failure events (WHFE) have been limited in using structured healthcare data from hospitalizations, and with little exploration of sociodemographic variation. The current study examined the impa...
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