Objective Artificial intelligence (AI) models may propagate harmful biases in performance
and hence negatively affect the underserved. We aimed to assess the degree to which data …

Objectives Leveraging artificial intelligence (AI) in conjunction with electronic health records
(EHRs) holds transformative potential to improve healthcare. However, addressing bias in …

The adoption of artificial intelligence (AI) algorithms is rapidly increasing in healthcare. Such
algorithms may be shaped by various factors such as social determinants of health that can …

The importance of social components of health has been emphasized both in epidemiology
and public health. This paper highlights the significant impact of social components on …

Objective The development of machine learning (ML) algorithms to address a variety of
issues faced in clinical practice has increased rapidly. However, questions have arisen …

We are at a pivotal moment in the development of healthcare artificial intelligence (AI), a
point at which enthusiasm for machine learning has not caught up with the scientific …

Artificial Intelligence (AI) can potentially impact many aspects of human health, from basic
research discovery to individual health assessment. It is critical that these advances in …

Background Artificial intelligence (AI) has repeatedly been shown to encode historical
inequities in healthcare. We aimed to develop a framework to quantitatively assess the …

Introduction Developments in Artificial Intelligence (AI) are adopted widely in healthcare.
However, the introduction and use of AI may come with biases and disparities, resulting in …

Asthma puts a tremendous overhead on healthcare. To enable effective preventive care to
improve outcomes in managing asthma, we recently created two machine learning models …