Medicine is at a disciplinary crossroads. With the rapid integration of Artificial Intelligence
(AI) into the healthcare field the future care of our patients will depend on the decisions we …

Background While artificial intelligence (AI) offers possibilities of advanced clinical
prediction and decision-making in healthcare, models trained on relatively homogeneous …

Artificial intelligence (AI) shows promise for improving basic and translational science,
medicine, and public health, but its success is not guaranteed. Numerous examples have …

Health equity is a primary goal of healthcare stakeholders: patients and their advocacy
groups, clinicians, other providers and their professional societies, bioethicists, payors and …

The emergence and increasing use of artificial intelligence and machine learning (AI/ML) in
healthcare practice and delivery is being greeted with both optimism and caution. We focus …

Artificial intelligence (AI) has an astonishing potential in assisting clinical decision making
and revolutionizing the field of health care. A major open challenge that AI will need to …

In healthcare, the development and deployment of insufficiently fair systems of artificial
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …

In this review, we address the issue of fairness in the clinical integration of artificial
intelligence (AI) in the medical field. As the clinical adoption of deep learning algorithms, a …

Population and public health are in the midst of an artificial intelligence revolution capable of
radically altering existing models of care delivery and practice. Just as AI seeks to mirror …

Artificial intelligence (AI) is poised to broadly reshape medicine, potentially improving the
experiences of both clinicians and patients. We discuss key findings from a 2-year weekly …