AIMC Topic: Radiology

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Enabling AI in Radiology: Evaluation of an AI Deployment Process.

Studies in health technology and informatics
Artificial intelligence (AI) is expected to transform healthcare systems and make them more sustainable. Despite the increased availability of AI tools for disease detection, evidence of their impact on healthcare organisations and patient care remai...

[Artificial intelligence in emergency radiology: fiction or reality?].

Revue medicale suisse
Artificial intelligence (AI) is a rapidly advancing technology in our society. The emergency radiology is an area facing an increase of the number of imaging studies and associated to the necessity to promptly deliver an accurate interpretation. The ...

Medical artificial intelligence for clinicians: the lost cognitive perspective.

The Lancet. Digital health
The development and commercialisation of medical decision systems based on artificial intelligence (AI) far outpaces our understanding of their value for clinicians. Although applicable across many forms of medicine, we focus on characterising the di...

Weakly Supervised Deep Learning in Radiology.

Radiology
Deep learning (DL) is currently the standard artificial intelligence tool for computer-based image analysis in radiology. Traditionally, DL models have been trained with strongly supervised learning methods. These methods depend on reference standard...

Clinical, Cultural, Computational, and Regulatory Considerations to Deploy AI in Radiology: Perspectives of RSNA and MICCAI Experts.

Radiology. Artificial intelligence
The Radiological Society of North of America (RSNA) and the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society have led a series of joint panels and seminars focused on the present impact and future directions of artificial i...

2023 Survey on User Experience of Artificial Intelligence Software in Radiology by the Korean Society of Radiology.

Korean journal of radiology
OBJECTIVE: In Korea, radiology has been positioned towards the early adoption of artificial intelligence-based software as medical devices (AI-SaMDs); however, little is known about the current usage, implementation, and future needs of AI-SaMDs. We ...