IMPORTANCE: The updated race and ethnicity reporting guidelines published in the AMA Manual of Style: A Guide for Authors and Editors highlight the importance of using specific racial and ethnic categories rather than generalized terms, promoting inc...
Spinal cord hemangioblastomas are rare, benign, intradural tumors that, despite their nonmalignant histopathology, can lead to substantial neurological morbidity. While disparities in outcomes based on race and socioeconomic status have been well-doc...
The role and use of race within health-related artificial intelligence (AI) and machine learning (ML) models have sparked increasing attention and controversy. Despite the complexity and breadth of related issues, a robust and holistic framework to g...
BACKGROUND: User demographics are often hidden in social media data due to privacy concerns. However, demographic information on substance use (SU) can provide valuable insights, allowing public health policy makers to focus on specific cohorts and d...
Historical racial and ethnic disparities in short-term exposure to ambient nitrogen dioxide (NO) have rarely been investigated, primarily due to the lack of spatiotemporally resolved NO data covering the historical period. In this study, we used publ...
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...
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