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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Peter Monteleone, MD, an interventional cardiologist, national director of cardiovascular research at Ascension Health, and assistant professor, UT Austin Dell School of Medicine, explained the use of artificial intelligence (AI) to independently identify an emergency stroke or pulmonary embolism (PE) finding on a CT scan and automatically alert critical care team members. His health system uses this type of AI for earlier activation of the pulmonary embolism response team (PERT).

AI critical care software revolutionizes emergency response

Ascension Health in Texas uses AI that can read CT scans for stroke and pulmonary embolism to activate care teams before the images even get into the PACS.

The ASNC team at the 2024 AMA meeting, Georgia Lawrence, JD, ASNC director of regulatory affairs; Suman Tandon, MD, FASNC, delegate to the AMA HOD and cardiac imager at NYU Langone; and Kathy Flood, ASNC CEO. #AMA #AMA24 #AMA2024 #AMAHOD #ASNC

ASNC supports AMA effort to limit use of AI in prior authorization decisions

The American Society of Nuclear Cardiology (ASNC) supports an AMA policy that condemns the use AI to make prior authorization decisions rather than a doctor or clinician.

The central illustration from a study that shows the impact of ECG AI algorithm study case and control selection to train artificial intelligence to better screening patients for cardiac amyloidosis. Image courtesy of JACC Advances.

Using ECG AI to find the cardiac amyloidosis needles in the haystack

Early detection of cardiac amyloidosis is leads to the best outcomes, but it is often missed until later stages. AI is being developed to help detect these patients earlier using ECG and echo.

Jagmeet Singh, MD, PhD, Professor of Medicine, Harvard Medical School, and Founding Director of the Resynchronization and Advanced Cardiac Therapeutics Program at Mass General Hospital, delivered a key note address at HRS 2024 on the future of artificial intelligence in EP and AI applications in cardiology. #HRS #EPeeps #HRS2024 #HRS24 #HealthAI

Embracing AI to enhance EP: Insights from cardiologist Jagmeet Singh

Jagmeet Singh, MD, delivered a keynote address at HRS 2024 on the future of AI in electrophysiology. He spoke to Cardiovascular Business, sharing additional thoughts about the topic.

doctor examines patient data on their tablet

Engineers team with cardiologist to rethink heart pump assessments

The group’s work is focused on how signal processing technologies and machine learning can track the health of VADs and the patients who need them. 

Eko Health, the California-based healthcare technology company known for its advanced stethoscopes, has received U.S. Food and Drug Administration (FDA) approval for a new artificial intelligence (AI) offering designed to detect low ejection fraction (EF).

Eko Health raises $41M to expand footprint of its AI-powered stethoscopes

Now that the company has gained FDA approval for multiple algorithms, Eko Health aims to reach as many patients as possible with its AI-powered devices.

The rapid rise of artificial intelligence (AI) has helped cardiologists, radiologists, nurses and other healthcare providers embrace precision medicine in a way that ensures more heart patients are receiving personalized care.

AI uses imaging results to ID high-risk TAVR patients with speed, accuracy

Researchers developed an advanced AI model capable of extracting measurements from unprocessed CT images in seconds. It then uses those data to evaluate the patient's mortality risk if they underwent TAVR.

HeartFlow Plaque Analysis

AI-based coronary plaque assessments 1 step closer to Medicare coverage

According to a new proposal, using AI to evaluate CCTA results and quantify plaque buildup is “reasonable and medically necessary” in certain clinical scenarios.

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Around the web

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Use of AI opportunistic screening in CT for cardiovascular disease

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

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New imaging protocols proposed to curb rise of cardiovascular infections

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