PURPOSE: Imaging diagnosis of stapes fixation (SF) is challenging owing to a lack of definite evidence. We developed a comprehensive machine learning (ML) model to identify SF on ultra-high-resolution CT.
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...
Automatic and accurate segmentation of pulmonary nodules in CT images can help physicians perform more accurate quantitative analysis, diagnose diseases, and improve patient survival. In recent years, with the development of deep learning technology,...
IEEE journal of biomedical and health informatics
Aug 7, 2023
Segmentation of intracranial aneurysms (IAs) is an important step for the diagnosis and treatment of IAs. However, the process by which clinicians manually recognize and localize IAs is overly labor intensive. This study aims to develop a deep-learni...
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.
RATIONALE AND OBJECTIVE: Image interpretation is a fundamental aspect of radiology. The treatment and management of patients relies on accurate and timely imaging diagnosis. However, errors in radiological reports can negatively impact on patient hea...
Journal of the American College of Radiology : JACR
Jul 23, 2023
PURPOSE: Artificial intelligence (AI) thoracic imaging applications are increasingly being deployed in low- and middle-income countries (LMICs). Radiologists have a critical gatekeeping role to ensure the effective and ethical implementation of AI so...
Journal of the American College of Radiology : JACR
Jul 14, 2023
There are two major areas for patient engagement in radiology artificial intelligence (AI). One is in the sharing of data for AI development; the second is the use of AI in patient care. In general, individuals support sharing deidentified data if us...