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. 

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Lack of transparency in AI research limits reproducibility, renders work 'worthless'

A recent analysis found that a significant amount of studies do not provide information pertaining to their raw data, source code or model. As a result, up to 97% of these studies do not produce systems that are fit to be used in real-world clinical scenarios. 

An example of artificial intelligence (AI) automated detection of a intracranial hemorrhage (ICH) in. a CT scan used to send alerts to the stroke acute care team before a radiologist even sees the exam. Example shown by TeraRecon at RSNA 2022.

VIDEO: Radiology AI aids acute care and other departments

Sanjay Parekh, PhD, senior market analyst with Signify Research, explains how some radiology AI is being adopted outside of radiology departments to improve care.

FDA move signals a forthcoming increase in the use of virtual and augmented reality devices in radiology

The applications for VR/AR devices are wide-ranging, and could be particularly beneficial in underserved areas where patients have less access to care and clinicians have fewer opportunities to train.

Example of AI automated detection and highlighting of critical lung findings on a chest X-ray for a possible lung cancer nodule and fibrosis. Example shown by AI vendor Lunit.

VIDEO: Radiology AI trends at RSNA 2022

Sanjay Parekh, PhD, senior market analyst with Signify Research, discusses trends in radiology AI seen on the expo floor and in sessions at RSNA 2022.

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AI-powered platform for heart failure detection gains FDA clearance

According to data submitted to the FDA, the platform has been linked to an accuracy of 90%, sensitivity of 87.8% and specificity of 83%.

AI is still one of the key technologies on the floor many radiologists want to learn more about. of the AI. A product rep discussing breast automated detection AI in the crowded Lunit booth at RSNA 2022.

9 technology trends and takeaways from RSNA 2022

Here are some interesting new technologies and key trends from the vast expo floor at the Radiological Society of North America 2022 meeting.

Jorge Soto, MD, chair of the RSNA Annual Meeting Program Planning Committee, chief of radiology, Boston Medical Center, and professor of medicine, Boston University School of Medicine, offers an overview of the trends, hot topics, and innovative research and technology at the Radiological Society of North America (RSNA) 2022 meeting.

VIDEO: Key takeaways from RSNA 2022

Jorge Soto, MD, chair of the RSNA Annual Meeting Program Planning Committee, chief of radiology, Boston Medical Center, offers an overview of the trends, hot topics, research and technology at the Radiological Society of North America (RSNA) 2022 meeting.

Dynamic lung air flow analysis just using X-ray without any contrast with new technology from 4D Medical.

PHOTO GALLERY: New technology and trends at RSNA 2022

Images from the Radiological Society of North America (RSNA) 2022 annual meeting Nov. 27- Dec. 1 in Chicago. The gallery includes new technologies and a look at sights around the world's largest radiology conference. 

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