The application of artificial intelligence (AI) in medical practice is spreading, especially in technologically dense fields such as radiology, which could consequently undergo profound transformations in the near future. This article aims to qualita...
The incorporation of artificial intelligence into radiological clinical workflow is on the verge of being realized. To ensure that these tools are effective, measures must be taken to educate radiologists on tool performance and failure modes. Additi...
OBJECTIVES: To investigate how a transition from free text to structured reporting affects reporting language with regard to standardization and distinguishability.
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 subfield of AI, progresses, concerns have arisen regarding the ...
OBJECTIVES: To map the clinical use of CE-marked artificial intelligence (AI)-based software in radiology departments in the Netherlands (n = 69) between 2020 and 2022.
Journal of the American College of Radiology : JACR
Jul 27, 2023
Despite the expert-level performance of artificial intelligence (AI) models for various medical imaging tasks, real-world performance failures with disparate outputs for various subgroups limit the usefulness of AI in improving patients' lives. Many ...
Journal of the American College of Radiology : JACR
Jul 25, 2023
In this white paper, the ACR Pediatric AI Workgroup of the Commission on Informatics educates the radiology community about the health equity issue of the lack of pediatric artificial intelligence (AI), improves the understanding of relevant pediatri...