The Digital Revolution in Cardiac Ischemia: Artificial Intelligence (AI)-Enhanced Detection, Diagnosis, and Risk...

Area of Science:

• Cardiology
• Artificial Intelligence
• Medical Imaging

Background:

• Traditional diagnostic tools for cardiac ischemia have limitations.
• Artificial intelligence (AI) offers new approaches to overcome these limitations.
• Machine learning and deep learning (DL) are advancing cardiac diagnostics.

Purpose of the Study:

• To review the impact of AI on cardiac ischemia diagnosis and management.
• To highlight AI's capabilities in various cardiac imaging modalities.
• To discuss the potential of AI in improving patient outcomes.

Main Methods:

• AI applications in analyzing coronary CT angiography for plaque quantification and stenosis.
• DL algorithms for fractional flow reserve computation.
• AI in cardiac MRI and perfusion imaging for myocardium segmentation and ischemia detection.
• Integration of wearable devices for continuous monitoring.

Main Results:

• AI, particularly convolutional neural networks, detects myocardial infarction with high accuracy.
• AI automates plaque quantification and stenosis assessment, reducing evaluation time.
• AI algorithms achieve expert-level performance in cardiac MRI and perfusion imaging.
• AI-enhanced tools often surpass traditional methods and expert interpretation.

Conclusions:

• AI is transforming cardiac ischemia management through earlier detection and accurate diagnosis.
• AI enables refined risk stratification and personalized prediction models.
• Despite challenges, AI integration promises to significantly improve patient outcomes in cardiac ischemia care.