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

Download Mobile App




Multimodal AI to Revolutionize Cardiovascular Disease Diagnosis and Treatment

By LabMedica International staff writers
Posted on 20 Oct 2025

Cardiovascular diseases remain the leading cause of death worldwide, and while artificial intelligence (AI) has shown promise in their diagnosis and management, most existing systems rely on a single data type such as ECGs or cardiac imaging. More...

This limits diagnostic accuracy and prevents algorithms from reflecting the comprehensive reasoning process that physicians use in clinical practice. Now, a new multimodal AI approach aims to overcome this limitation by integrating diverse clinical data sources to deliver more accurate and personalized cardiovascular insights.

The study, led by West China Hospital of Sichuan University (Sichuan, China) and the University of Copenhagen (Copenhagen, Denmark), reviewed over 150 studies demonstrating the potential of multimodal AI in cardiovascular medicine. This next-generation approach fuses complementary data modalities—such as echocardiography, computed tomography, magnetic resonance imaging, and genomics—to enhance diagnostic precision. For example, a transformer-based neural network combining chest radiographs with clinical variables simultaneously identified 25 critical pathologies in intensive-care patients, achieving an average diagnostic accuracy (AUC) of 0.77.

The review, published in Precision Clinical Medicine, showed that multimodal AI can also reveal new biological insights. By integrating cardiac MRI with genome-wide association data, researchers identified novel genetic loci linked to aortic valve function. In addition to diagnosis, these models refined treatment decisions—predicting which heart-failure patients would respond to cardiac resynchronization therapy and identifying those unlikely to benefit from mitral-valve repair, thereby improving patient selection and treatment efficiency.

Emerging multimodal algorithms also enable continuous health monitoring by merging data from wearable devices, mobile applications, and electronic health records. These tools can detect early signs of deterioration, deliver automated health coaching, and reduce readmission rates. The authors estimate that adopting multimodal AI in clinical practice could reduce cardiovascular healthcare costs by 5%−10% over five years through improved efficiency and fewer complications.


Gold Member
Blood Gas Analyzer
Stat Profile pHOx
POC Helicobacter Pylori Test Kit
Hepy Urease Test
8-Channel Pipette
SAPPHIRE 20–300 µL
Autoimmune Liver Diseases Assay
Microblot-Array Liver Profile Kit
Read the full article by registering today, it's FREE! It's Free!
Register now for FREE to LabMedica.com and get access to news and events that shape the world of Clinical Laboratory Medicine.
  • Free digital version edition of LabMedica International sent by email on regular basis
  • Free print version of LabMedica International magazine (available only outside USA and Canada).
  • Free and unlimited access to back issues of LabMedica International in digital format
  • Free LabMedica 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

Molecular Diagnostics

view channel
Image: The Simoa p-Tau 217 research assay measures phosphorylated tau in blood (Photo courtesy of Quanterix)

Ultra-Sensitive Blood Biomarkers Enable Population-Scale Insights into Alzheimer’s Pathology

Accurately estimating how many people carry Alzheimer’s disease pathology has long been a challenge, as traditional methods rely on small, clinic-based samples rather than the general population.... Read more

Hematology

view channel
Image: Residual leukemia cells may predict long-term survival in acute myeloid leukemia (Photo courtesy of Shutterstock)

MRD Tests Could Predict Survival in Leukemia Patients

Acute myeloid leukemia is an aggressive blood cancer that disrupts normal blood cell production and often relapses even after intensive treatment. Clinicians currently lack early, reliable markers to predict... Read more
Copyright © 2000-2026 Globetech Media. All rights reserved.