Artificial Intelligence

Artificial intelligence (AI) is becoming a crucial component of healthcare to help augment physicians and make them more efficient. In medical imaging, it is helping radiologists more efficiently manage PACS worklists, enable structured reporting, auto detect injuries and diseases, and to pull in relevant prior exams and patient data. In cardiology, AI is helping automate tasks and measurements on imaging and in reporting systems, guides novice echo users to improve imaging and accuracy, and can risk stratify patients. AI includes deep learning algorithms, machine learning, computer-aided detection (CAD) systems, and convolutional neural networks. 

Cardiology, radiology specialists debate CCTA’s rise as a go-to imaging modality for CAD

CCTA is being utilized more and more for the diagnosis and management of suspected coronary artery disease. An international group of specialists shared their perspective on this ongoing trend.

translate language

Can large language models break language barriers in radiology reports?

With the growing demand for virtual care and an increasingly mobile population, the need to improve communication with non-English-speaking patients is immense. 

AI in healthcare

Most patients want to know if AI is involved in their care

“With this signal about the public’s preference for notification, the question for health systems and policymakers is not whether to notify patients but when and how.” 

Ischemic stroke shown in CT scans. Image courtesy of RSNA

New algorithm is twice as accurate at predicting stroke timing compared to the standard of care

Determining stroke onset is critical for management, as there is a small window of time for initiating treatment that can inhibit damage.

Kate Hanneman, MD, chair of the Radiological Society of North America (RSNA) program planning committee, explains some of the key trends she saw in sessions during RSNA 2024. #RSNA #RSNA24 #RSNA2024

RSNA 2024 Program Chair Kate Hanneman highlights key trends in radiology

The cardiac radiologist and associate professor at the University of Toronto offered insights into key themes from the conference. 

How AI 'cheating' could impact algorithm reliability

A new study on the implications of AI shortcutting has experts raising concerns about the integration of the technology into medicine.

Thumbnail

New AI program delivers rapid, accurate echo video assessments

The new technology shows early potential to make a significant impact on imaging workflows and patient care. 

Thumbnail

Do large language models help or hinder workflows related to radiology reports?

Some have suggested LLMs could reword reports to improve patient comprehension, but whether this is a feasible option remains unknown. 

Around the web

CCTA is being utilized more and more for the diagnosis and management of suspected coronary artery disease. An international group of specialists shared their perspective on this ongoing trend.

The new technology shows early potential to make a significant impact on imaging workflows and patient care. 

Richard Heller III, MD, RSNA board member and senior VP of policy at Radiology Partners, offers an overview of policies in Congress that are directly impacting imaging.