Purpose Artificial intelligence (AI) in radiology has been a subject of heated debate. The
external perception is that algorithms and machines cannot offer better diagnosis than …

With artificial intelligence (AI) precipitously perched at the apex of the hype curve, the
promise of transforming the disparate fields of healthcare, finance, journalism, and security …

Artificial intelligence (AI) is already widely employed in various medical roles, and ongoing
technological advances are encouraging more widespread use of AI in imaging. This is …

Since the introduction of artificial intelligence (AI) in radiology, the promise has been that it
will improve health care and reduce costs. Has AI been able to fulfill that promise? We …

An increasing number of unanswered questions made us unsettled about the evolution of
radiology and its current ability to keep up with the pace of healthcare transformation. The …

Despite the expert-level performance of AI models for various medical imaging tasks, real-
world performance failures with disparate outputs for various subgroups limit the usefulness …

Artificial intelligence (AI) and machine learning (ML) are increasingly used in radiology
research to deal with large and complex imaging data sets. Nowadays, ML tools have …

OBJECTIVE. The purpose of this article is to discuss the problem of interpretability of artificial
intelligence (AI) and highlight the need for continuing scientific discovery using AI algorithms …

The arrival of artificially intelligent systems into the domain of medical imaging has focused
attention and sparked much debate on the role and responsibilities of the radiologist …

Emergency Radiology is a unique branch of imaging, as rapidity in the diagnosis and
management of different pathologies is essential to saving patients' lives. Artificial …