A primer in artificial intelligence in cardiovascular medicine

Area of Science:

• Cardiovascular Medicine
• Artificial Intelligence
• Machine Learning

Background:

• Machine learning (ML)-based artificial intelligence (AI) is rapidly advancing due to increased computational power and data storage.
• AI adoption is growing across various sectors, including healthcare, with significant investments in AI-driven hospitals.
• Cardiovascular disease diagnosis and treatment can benefit from AI's ability to analyze complex datasets and uncover hidden patterns.

Purpose of the Study:

• To introduce the fundamentals of modern ML-based AI to the cardiovascular community.
• To explain commonly used AI algorithms relevant to cardiovascular applications.
• To summarize current and future AI applications in cardiovascular disease diagnosis and treatment.

Main Methods:

• Review of machine learning algorithms and their applications in cardiovascular medicine.
• Synthesis of existing literature on AI in cardiovascular research and clinical practice.
• Explanation of AI concepts for professionals in patient care, education, and science.

Main Results:

• AI has the potential to significantly enhance traditional statistical analyses in cardiovascular medicine.
• Early applications of AI in the cardiovascular field show promising results for diagnosis and treatment.
• There is a knowledge gap among cardiovascular professionals regarding AI basics and applications.

Conclusions:

• AI, specifically ML, offers valuable tools for advancing cardiovascular care.
• Educating cardiovascular professionals on AI is crucial for its effective implementation.
• Future applications of AI are expected to further revolutionize cardiovascular disease management.