Abstract
Conventional echocardiography traditionally relies on population-derived reference values and dichotomous classification schemes that do not fully account for individual patient characteristics or disease complexity. Artificial intelligence (AI) is driving a paradigm shift toward precision echocardiography by enabling patient-specific cardiovascular assessment through the integration of phenotypic, clinical, and biological data. This review examines how AI is transforming echocardiography from a population-based test into a patient-specific assessment tool that supports precision cardiovascular care. It highlights three clinical applications with potential clinical impact: Heart Failure with Preserved Ejection Fraction phenogrouping for targeted therapy selection, cardio-oncology surveillance with individualized cardiotoxicity risk prediction, and cardiomyopathy risk stratification for personalized sudden cardiac death prevention. For each application, it describes the clinical challenge, the AI-enabled precision solution, and its potential clinical impact. It also outlines a practical roadmap for clinical adoption. Precision echocardiography, powered by AI, holds promise for transforming cardiovascular imaging and diagnostics by enabling more patient-specific assessment, earlier disease detection, and personalized therapeutic strategies.
| Original language | American English |
|---|---|
| Pages (from-to) | 1-16 |
| Number of pages | 16 |
| Journal | Diagnostics |
| Volume | 16 |
| Issue number | 5 |
| State | Published - 26 Feb 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 3 Good Health and Well-being
Keywords
- precision medicine
- artificial intelligence
- precision echocardiography
- cardiovascular phenotyping
- personalized cardiovascular care
Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver