Artificial Intelligence in Clinics: Enhancing Cardiology Practice.

Area of Science:

• Cardiology
• Medical Informatics
• Artificial Intelligence

Background:

• Artificial intelligence (AI) technologies, including large language models, are rapidly advancing and integrating into various societal sectors.
• AI demonstrates capabilities in image and voice recognition, natural language processing, and complex data analysis.
• Healthcare settings are increasingly adopting AI, poised to significantly alter clinical workflows.

Purpose of the Study:

• To review the applications of AI in cardiology.
• To examine how AI integration can enhance clinical workflows and patient care.
• To highlight the potential of AI in improving the diagnosis and treatment of cardiovascular diseases.

Main Methods:

• Review of current AI applications in cardiology.
• Analysis of AI's role in patient interviews, diagnostic tests (e.g., ECGs, X-rays), and specialized areas like auscultation and gait analysis.
• Discussion of AI's potential impact on cardiovascular disease management.

Main Results:

• AI is being integrated into cardiology for tasks such as patient interviews, interpretation of diagnostic tests, and analysis of complex data like gait.
• AI facilitates beyond-human interpretation of medical data and improves recognition of challenging observations.
• Despite implementation barriers, AI collaboration is expected to enhance diagnostic accuracy and treatment efficacy for cardiovascular conditions.

Conclusions:

• AI integration in cardiology promises to streamline clinical practices, leading to more accurate diagnoses and treatments.
• Collaboration between physicians and AI is anticipated to improve patient care for conditions including ischemic heart disease, valvular heart disease, arrhythmias, and heart failure.
• Understanding and adopting AI advancements is crucial for optimizing medical practices and benefiting both healthcare providers and patients.