Advancements in Artificial Intelligence in Noninvasive Cardiac Imaging: A Comprehensive Review
Problem
A literature review examining how AI can improve analysis, image quality, processing speed and diagnostic accuracy across noninvasive cardiac imaging modalities (echocardiography, MRI, CT, nuclear).
Why it matters
Faster, more accurate cardiac imaging diagnosis directly affects patient outcomes in heart disease.
What the AI did
The paper reviews machine learning and deep learning applications that enhance image quality, accelerate processing and improve diagnostic accuracy in cardiac imaging workflows.
Results
Review finds AI integration enhances image quality and processing; detailed metrics not stated in source (abstract truncated).
Impact
Evidence supports AI's growing role in cardiac imaging diagnostics, per the review's findings.
Record
| Venue | Clinical Cardiology |
|---|---|
| Published | 2025 |
| Work type | article |
| Authors | Oluwaremilekun Zeth Tolu-Akinnawo, Francis Ezekwueme, Olukunle Samuel Omolayo, Sasha Batheja, Toluwalase Awoyemi |
| Citations | 40 (OpenAlex, at import time) |
| References | 55 |
| Model or method | not stated in source |
| Organization | not stated in source |
| Primary source | https://doi.org/10.1002/clc.70087 |
| Open access | gold |
| Keywords | artificial intelligence, cardiac imaging, echocardiography, MRI, CT, diagnostics |
Importance rating
significant — thousands to millions affected
AI across echocardiography, MRI, CT, nuclear imaging to improve diagnostic workflows and patient outcomes; review claims transformative potential for cardiac diagnosis, but no scale quantified.