Artificial Intelligence Echocardiography in Resource-Limited Regions: Applications and Challenges.

Area of Science:

• Cardiology
• Medical Imaging
• Artificial Intelligence

Background:

• Artificial intelligence (AI) is transforming cardiac imaging modalities like echocardiography.
• AI adoption remains limited in resource-constrained healthcare settings globally.

Purpose of the Study:

• To explore the potential benefits and challenges of implementing AI-aided echocardiography (AIE) in resource-limited regions.
• To identify key factors influencing AIE adoption and its impact on healthcare equity.

Main Methods:

• Review of early experiences and case studies involving AI implementation in echocardiography.
• Analysis of potential advantages and barriers to AIE in resource-limited contexts.

Main Results:

• AIE can enhance echocardiographic image acquisition, interpretation, and patient triage.
• Significant challenges include limited data accessibility for AI model development, physician hesitancy, and regulatory hurdles.

Conclusions:

• AI-aided echocardiography holds promise for improving health equity and access to advanced cardiac imaging in underserved regions.
• Overcoming implementation barriers requires substantial investment and strategic planning to achieve cost savings and widespread adoption.