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Radiology

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Self-supervised multi-modal training from uncurated images and reports enables monitoring AI in radiology.

Medical image analysis
The escalating demand for artificial intelligence (AI) systems that can monitor and supervise human errors and abnormalities in healthcare presents unique challenges. Recent advances in vision-language models reveal the challenges of monitoring AI by...

A Survey of Publicly Available MRI Datasets for Potential Use in Artificial Intelligence Research.

Journal of magnetic resonance imaging : JMRI
Artificial intelligence (AI) has the potential to bring transformative improvements to the field of radiology; yet, there are barriers to widespread clinical adoption. One of the most important barriers has been access to large, well-annotated, widel...

Analysis of ChatGPT publications in radiology: Literature so far.

Current problems in diagnostic radiology
OBJECTIVE: To perform a detailed qualitative and quantitative analysis of the published literature on ChatGPT and radiology in the nine months since its public release, detailing the scope of the work in the short timeframe.

Radiology Residents' Perceptions of Artificial Intelligence: Nationwide Cross-Sectional Survey Study.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) is transforming various fields, with health care, especially diagnostic specialties such as radiology, being a key but controversial battleground. However, there is limited research systematically examining th...

Update on ethical aspects in clinical research: Addressing concerns in the development of new AI tools in radiology.

Radiologia
The analysis of ethical aspects in clinical research has always been a challenge and has required constant updates. In short, research ethics is the set of specific principles, rules, and norms of behavior that a research community has decided are ap...

Impact of deep learning on radiologists and radiology residents in detecting breast cancer on CT: a cross-vendor test study.

Clinical radiology
AIM: To investigate the effect of deep learning on the diagnostic performance of radiologists and radiology residents in detecting breast cancers on computed tomography (CT).

Knowledge and Perception of the Use of AI and its Implementation in the Field of Radiology: Cross-Sectional Study.

Journal of medical Internet research
BACKGROUND: Artificial Intelligence (AI) has been developing for decades, but in recent years its use in the field of health care has experienced an exponential increase. Currently, there is little doubt that these tools have transformed clinical pra...