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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AI predicts mortality risk based on ECG results with 85% accuracy

The model estimated mortality risk for more than 244,000 patients in Alberta, Canada, who had an ECG taken after a related health incident. 

Echocardiography expert Patricia A. Pellikka, MD, discussed the trend of increasing artificial intelligence (AI) integration in cardiac ultrasound with Cardiovascular Business at American College of Cardiology (ACC) 2023 meeting.

AI's growing impact on echocardiography

Cardiology has the second largest number of FDA-cleared AI algorithms, and many of them are for cardiac ultrasound. Echocardiography expert Patricia A. Pellikka, MD, discusses this trend and how AI is helping improve echo.

Large study finds high rates of nonadherence to statin recommendations; women especially averse

Many patients who would clearly benefit by lowered LDL cholesterol levels are choosing to forgo first-time recommendations for statin regimens, according to a population-level study. 

artificial intelligence AI deep learning

AI model uses DNA to predict AFib, heart failure

Scientists were able to identify a total of 21 genes linked to cardiovascular conditions such as AFib and heart failure.

The evolution of care: 3 key takeaways from a new survey of cardiologists, health leaders and CVD patients

The report, developed by Abbott, examined everything from AI to social determinants of health. One key finding was that patients grade their overall satisfaction with a physician or hospital based on much more than the effectiveness of their treatment. 

A team of cardiologists from Cleveland Clinic and Stanford University recently tested ChatGPT, the popular artificial intelligence (AI) model, to see if it could accurately answer questions about preventive cardiology and cardiovascular disease. The model performed well, only missing a handful of questions, and the researchers concluded that ChatGPT showed considerable potential. Cleveland Clinic cardiologist Ashish Sarraju, MD, was the lead author of that study. #ChartGPT

ChatGPT and cardiology: A close look at the strengths and weaknesses of AI chatbots

Ashish Sarraju, MD, a cardiologist with Cleveland Clinic, discussed his recent research on ChatGPT, its potential to change patient care and more. 

The integration of artificial intelligence (AI) into radiology PACS and enterprise imaging systems has become a big topic of discussion with IT vendors over the past couple years. This has become a bigger question from hospitals and radiology groups as there are now about 400 radiology related AI algorithms that have U.S. Food and Drug Administration (FDA) clearance. Amy Thompson, a senior analyst at Signify Research, is monitoring AI trends in radiology and discusses trends.

Trends in the adoption and integration of AI into radiology workflows

Amy Thompson, a senior analyst at Signify Research, explains why AI adoption has been slow in radiology, common barriers and trends in the market.

Ed Nicol, MD, consultant cardiologist and honorary senior clinical lecturer with Kings College London and president-elect of the Society of Cardiovascular Computed Tomography (SCCT), explained artificial intelligence (AI) in cardiac CT is here to stay and its use is expanding. He noted that one AI-based algorithm is already included in recent cardiology guidelines and more will likely follow. #SCCT

Cardiac imagers need to understand AI as it enters clinical use and ACC guidelines

Most FDA-cleared AI algorithms are related to radiology and cardiology, meaning radiologists and cardiologists need to make an effort to learn how these technologies work.

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