Development and Validation of Echocardiography Artificial Intelligence Models: A Narrative Review

Area of Science:

• Cardiology
• Medical Imaging
• Artificial Intelligence

Background:

• Echocardiography is crucial for cardiac assessment but suffers from operator variability.
• Artificial intelligence (AI) integration offers potential to standardize echocardiographic interpretation and improve efficiency.
• AI applications in echocardiography range from image acquisition to prognostic stratification.

Purpose of the Study:

• To provide a comprehensive overview of AI model development and validation for echocardiography.
• To explore current challenges in AI implementation within echocardiography.
• To outline future directions for AI in echocardiographic practice.

Main Methods:

• This narrative review synthesizes existing literature on AI in echocardiography.
• It focuses on the essential steps for developing and validating AI models.
• The review examines challenges and future prospects.

Main Results:

• AI models show promise in assisting echocardiographic image acquisition, disease detection, and measurement automation.
• Despite growing interest, rigorous development and validation practices for AI in echocardiography are often not well-described.
• Standardized approaches are needed for safe and effective AI deployment.

Conclusions:

• AI has the potential to revolutionize echocardiography by enhancing consistency and efficiency.
• Clear guidelines for AI model development and validation are essential for clinical adoption.
• Future research should focus on addressing current challenges and exploring novel AI applications in echocardiography.