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 hp
Sign In
Advertise with Us
Sekisui Diagnostics UK Ltd.

Download Mobile App




AI-Enabled ECG Analysis Effectively Predicts Right-Side Heart Issues

By HospiMedica International staff writers
Posted on 05 Jan 2024

Traditional methods to assess the health of the heart’s right ventricle which sends blood to the lungs usually fall short. In a milestone study, researchers have leveraged the power of artificial intelligence (AI) to enhance the assessment of the heart’s right ventricle.

Researchers from the Icahn School of Medicine at Mount Sinai (New York, NY, USA) examined the efficacy of AI-enabled electrocardiogram (AI-ECG) analysis in detecting right-side heart complications. The study utilized a deep-learning ECG (DL-ECG) model, which was trained with harmonized data from 12-lead ECGs and cardiac magnetic resonance imaging (MRI) measurements. Conducted on an extensive dataset from the UK Biobank, the study's findings were further validated across various centers within the Mount Sinai Health System. The research focused on gauging the model's precision in identifying heart ailments and its influence on the survival rates of patients.

According to the researchers, while AI provides enhanced cardiac insights from widely used tools like ECGs, this approach is still in its infancy and isn't meant to substitute more advanced diagnostic methods. They have emphasized the need for additional studies to confirm the tool's efficacy and safe integration into clinical practices. Moreover, the team highlighted that the predictive results could vary among different demographics, depending on the quality and scope of the ECG and MRI data employed. The researchers plan to perform comprehensive validations of the DL-ECG models across diverse populations to ensure its widespread relevance and to verify its clinical effectiveness in diagnosing conditions such as pulmonary hypertension, congenital heart defects, and various cardiomyopathies.

“Our findings mark a significant leap forward in right heart health assessment, offering a glimpse into a future where AI plays a pivotal role in early and accurate diagnosis. The study stands out for applying AI to standard ECG data, predicting right ventricular function and size numerically,” said senior author Girish Nadkarni, MD, MPH, Irene and Dr. Arthur M. Fishberg Professor of Medicine at Icahn Mount Sinai.

“This novel method could expedite the identification of heart problems, especially in the right ventricle, and potentially lead to earlier and more effective treatment. It holds particular importance for patients with congenital heart disease, who often face issues in the right ventricle,” added co-first author Son Q. Duong MD, MS, Assistant Professor of Pediatrics (Pediatric Cardiology) at Icahn Mount Sinai.

Related Links:
Icahn School of Medicine at Mount Sinai

Platinum Member
STI Test
Vivalytic Sexually Transmitted Infection (STI) Array
Gold Member
Disposable Protective Suit For Medical Use
Disposable Protective Suit For Medical Use
Cardiograph Device
PageWriter TC35
X-Ray System
Leonardo DR mini III
Read the full article by registering today, it's FREE! It's Free!
Register now for FREE to HospiMedica.com and get access to news and events that shape the world of Hospital Medicine.
  • Free digital version edition of HospiMedica International sent by email on regular basis
  • Free print version of HospiMedica International magazine (available only outside USA and Canada).
  • Free and unlimited access to back issues of HospiMedica International in digital format
  • Free HospiMedica International Newsletter sent every week containing the latest news
  • Free breaking news sent via email
  • Free access to Events Calendar
  • Free access to LinkXpress new product services
  • REGISTRATION IS FREE AND EASY!
Click here to Register








Channels

Surgical Techniques

view channel
Image: Miniaturized electric generators based on hydrogels for use in biomedical devices (Photo courtesy of HKU)

Hydrogel-Based Miniaturized Electric Generators to Power Biomedical Devices

The development of engineered devices that can harvest and convert the mechanical motion of the human body into electricity is essential for powering bioelectronic devices. This mechanoelectrical energy... 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 Quantra Hemostasis System has received US FDA special 510(k) clearance for use with its Quantra QStat Cartridge (Photo courtesy of HemoSonics)

Critical Bleeding Management System to Help Hospitals Further Standardize Viscoelastic Testing

Surgical procedures are often accompanied by significant blood loss and the subsequent high likelihood of the need for allogeneic blood transfusions. These transfusions, while critical, are linked to various... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.