Exploring the Potential of AI and Augmented Reality in Cardiovascular Disease Management: A Narrative Review

Area of Science:

• Cardiovascular Medicine
• Medical Technology
• Health Informatics

Background:

• Cardiovascular diseases (CVDs) are a leading global cause of death, necessitating personalized treatment strategies.
• Artificial intelligence (AI) and augmented reality (AR) are emerging technologies transforming cardiovascular medicine and surgery.
• AI models, including machine learning and deep learning, are crucial for patient risk prediction, survival analysis, and risk stratification.

Purpose of the Study:

• To review the current applications of AI and AR in cardiovascular disease management.
• To highlight the potential of these technologies in improving diagnostic imaging and risk prediction.
• To identify gaps in current research and suggest future directions.

Main Methods:

• A comprehensive literature search was performed on PubMed and Google Scholar (2003-2024).
• Keywords included "cardiovascular disease," "artificial intelligence," "augmented reality," "diagnostic imaging," and "risk prediction."
• Studies were selected based on clinical relevance, title/abstract review, and full-text evaluation.

Main Results:

• AI and AR are increasingly utilized in cardiovascular disease management, enhancing image interpretation and documentation.
• Techniques like Convolutional Neural Networks (CNNs) and Natural Language Processing (NLP) improve image analysis.
• Despite promising applications, a lack of rigorous evaluation necessitates further large-scale trials.

Conclusions:

• AI and AR offer significant potential for personalized cardiovascular care and improved patient outcomes.
• Further research and large-scale clinical trials are essential to validate the efficacy and safety of AI/AR models.
• This review provides insights into recent advancements and future research opportunities in AI and AR for cardiology.