Diversity, equity, and inclusion (DEI) is both a critical ingredient and moral imperative in
shaping the future of radiology artificial intelligence (AI) for improved patient care, from …

Artificial intelligence (AI) holds promise for helping patients access new and individualized
health care pathways while increasing efficiencies for health care practitioners. Radiology …

Arkadiusz Sitek, PhD, holds the position of Associate Investigator in the radiology
department at Massachusetts General Hospital and Harvard Medical School. His work …

In the ubiquitous media coverage of artificial intelligence (AI) and machine learning,
radiology has emerged as the poster child for professions that will potentially be rendered …

The 2018 RSNA Summit on AI in Radiology brought together a diverse group of
stakeholders to identify and prioritize areas of need related to artificial intelligence in …

Scarce or absent radiology resources impede adoption of artificial intelligence (AI) for
medical imaging by resource-poor health institutions. They face limitations in local …

Rationale and Objectives With a track record of innovation and unique access to digital data,
radiologists are distinctly positioned to usher in a new medical era of artificial intelligence …

Commercially available artificial intelligence (AI) algorithms outside of health care have
been shown to be susceptible to ethnic, gender, and social bias, which has important …

Although recent scientific studies suggest that artificial intelligence (AI) could provide value
in many radiology applications, much of the hard engineering work required to consistently …

A common theme throughout this issue is the promise of artificial intelligence (AI) to impact
nearly every step of the imaging value chain, from order placement to scheduling, image …