We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us
Sekisui Diagnostics .

Download Mobile App

AI from Patient ECGs Can Detect Cardiovascular Disease Risks Sooner, Suggests Study

By HospiMedica International staff writers
Posted on 26 Oct 2023
Print article
Image: A new study suggests ECG-AI can detect cardiovascular disease risks sooner (Photo courtesy of 123RF)
Image: A new study suggests ECG-AI can detect cardiovascular disease risks sooner (Photo courtesy of 123RF)

Atherosclerotic cardiovascular disease, characterized by arteries that are narrowed or clogged due to fatty deposits, is the number one cause of death worldwide. Often, the condition is driven by coronary artery disease, which many people may have without even knowing it. Tools available to clinicians like the pooled cohort equation are used to evaluate a patient's 10-year risk of heart attacks and strokes, although these methods are not without flaws. Electrocardiograms (ECGs), which record the electrical activity of the heart, are commonly used tests. Artificial intelligence (AI) has the ability to recognize and analyze hidden disease patterns in these electrical signals. Now, a new study suggests that AI applied to patient ECGs could offer a more efficient way to assess the risk of heart disease.

According to the research, AI algorithms trained on ECG data can detect potential risks much earlier than existing risk-calculation methods. They can identify symptoms of coronary artery disease like arterial calcification and obstructions, as well as signs of previous heart attacks. The ECG-based AI for evaluating coronary artery disease risk was jointly created by at Mayo Clinic (Rochester, MN, USA) and Anumana, Inc. (Cambridge, MA, USA) using a retrospective analysis of electronic medical records from over seven million U.S. patients to train three distinct AI models. These models were designed to spot coronary artery calcium, arterial blockages, and poor movement in segments of the heart's left ventricle, which is an indicator of a past heart attack.

"Used together, the three independent ECG-AI models predicted which patients had a high risk of hidden coronary artery disease, and therefore a high risk of having a heart attack. This is important information to guide our conversations with patients at the point of care, especially since the AI was useful in calculating these risks for as short as three years," said Francisco Lopez-Jimenez, M.D., a cardiologist at Mayo Clinic. "Used alone, the pooled cohort equation estimates the 10-year risk of developing cardiovascular disease. The addition of ECG-AI to see hidden risks sooner has the potential to save more lives. This model may also help identify people who do not know they have coronary disease who may benefit from lifesaving therapies."

Related Links:
Mayo Clinic 
Anumana, Inc. 

Platinum Supplier
Real-Time Diagnostics Onscreen Viewer
GEMweb Live
Specimen Collection & Transport
Medical Monitor
Gold Supplier
12-Channel ECG

Print article


Surgical Techniques

view channel
Image: AI-based colonoscopy methods can significantly improve detection of colorectal neoplasia (Photo courtesy of 123RF)

AI Transforms Colonoscopy by Improving Detection and Reducing Missed Rates

Colorectal cancer ranks among the top three most common types of cancer globally and is a significant factor in cancer-related deaths. A primary strategy to reduce colorectal cancer incidence involves... Read more

Patient Care

view channel
Image: The newly-launched solution can transform operating room scheduling and boost utilization rates (Photo courtesy of Fujitsu)

Surgical Capacity Optimization Solution Helps Hospitals Boost OR Utilization

An innovative solution has the capability to transform surgical capacity utilization by targeting the root cause of surgical block time inefficiencies. Fujitsu Limited’s (Tokyo, Japan) Surgical Capacity... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more

Point of Care

view channel
Image: The new eye-safe laser technology can diagnose traumatic brain injury (Photo courtesy of 123RF)

Novel Diagnostic Hand-Held Device Detects Known Biomarkers for Traumatic Brain Injury

The growing need for prompt and efficient diagnosis of traumatic brain injury (TBI), a major cause of mortality globally, has spurred the development of innovative diagnostic technologies.... Read more
Copyright © 2000-2023 Globetech Media. All rights reserved.