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AI-Enabled Precision Echocardiography: Toward Personalized Cardiovascular Care

Research output: Contribution to journal › Review article › peer-review

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 languageAmerican English
Pages (from-to)1-16
Number of pages16
JournalDiagnostics
Volume16
Issue number5
StatePublished - 26 Feb 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • precision medicine
  • artificial intelligence
  • precision echocardiography
  • cardiovascular phenotyping
  • personalized cardiovascular care

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