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. 

Artificial intelligence (AI) analysis from a remote ECG monitor showing the AI generated report on the Philips Cardiologs system, during a demonstration of the technology at Heart Rhythm 2023. Photo by Dave Fornell

AI correctly IDs ventricular arrhythmias in 88% of patients with sustained VT

New research suggests AI could offer physicians a new, state-of-the-art approach to sudden cardiac arrest risk management.

The proliferation of artificial intelligence (AI) in healthcare includes numerous algorithms for electrophysiology (EP). Jagmeet Singh, MD, Professor of Medicine, Harvard Medical School, and founding director of the Resynchronization and Advanced Cardiac Therapeutics Program and Mass General Hospital, spoke with Cardiovascular Business at Heart Rhythm 2023 to explain how AI is being used in EP. #HRS2023 #HRS #AI

AI gaining popularity in electrophysiology

There are now numerous AI algorithms for electrophysiology. Jagmeet Singh, MD, examined how this advanced technology is being applied.

An example of HeartFlow's new RoadMap Stenosis software that uses artificial intelligence (AI) to show areas of interest for possible stenting based on a patient's CT scan and FFR-CT. This software is still undergoing beta testing at several hospitals and will likely be rolled out commercially later in 2023.

Cardiology has embraced AI more than most other specialties

Cardiology is linked to the second largest group of FDA-cleared clinical AI algorithms, and the number is still growing. 

Marcelo DiCarli, MD, chief, division of nuclear medicine and molecular imaging, executive director for the cardiovascular imaging program, Brigham and Women's Hospital, discusses how artificial intelligence (AI) is impacting cardiac imaging.

What is the ROI for adopting AI in cardiac imaging?

Marcelo DiCarli, MD, and Rob Beanlands, MD, discussed the long-term value of investing in the development and implementation of AI technologies. 

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AI model predicts LVEF during routine coronary angiograms

The video-based deep neural network showed potential for limiting invasive exams and improving patient care. 

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ChatGPT shows ‘remarkable ability’ to process thoracic surgery data, could help with training and patient care

A research lab led by a veteran cardiothoracic surgeon found that ChatGPT—particularly the GPT-4 model—could 'potentially revolutionize' training in the years ahead. 

AI specialists focused on cardiology bring in industry veteran to be executive chairman of the board

Scott Huennekens, who has more than 25 years of experience in the medical device industry, is the second addition Elucid has made to its board of directors in the last six months. 

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AI dramatically reduces radiologists’ rate of missed incidental pulmonary embolism on routine CT

The commercial software also reduced the median detection and notification time for incidental PE in flagged scans from “several days” down to just 1 hour.

Around the web

Ron Blankstein, MD, professor of radiology, Harvard Medical School, explains the use of artificial intelligence to detect heart disease in non-cardiac CT exams.

Eleven medical societies have signed on to a consensus statement aimed at standardizing imaging for suspected cardiovascular infections.