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Digitalomics: Towards Artificial Intelligence / Machine Learning-Based Precision Cardiovascular Medicine.

Akihiro Nomura1,2,3, Yasuaki Takeji2, Masaya Shimojima2

  • 1College of Transdisciplinary Sciences for Innovation, Kanazawa University.

Circulation Journal : Official Journal of the Japanese Circulation Society
|February 2, 2025
PubMed
Summary
This summary is machine-generated.

Digitalomics integrates diverse data for personalized cardiovascular risk assessment. Artificial intelligence and machine learning (AI/ML) enhance this approach, particularly through digital phonocardiography and AI text generators, advancing precision cardiovascular medicine.

Keywords:
Artificial intelligenceDigitalomicsGenerative AIMachine learningPhonocardiography

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Area of Science:

  • Cardiovascular Medicine
  • Digital Health
  • Artificial Intelligence

Background:

  • Traditional -omics technologies offer molecular insights into cardiovascular diseases.
  • Digitalomics integrates multimodal data (physiological, imaging, EHR, wearables) with multiomics.
  • AI/ML are key analytical tools for comprehensive health frameworks.

Purpose of the Study:

  • To review AI/ML applications in cardiovascular medicine within the digitalomics framework.
  • To highlight digital phonocardiography (PCG) and AI text generators as promising tools.
  • To discuss challenges and future directions for AI/ML integration in precision cardiovascular medicine.

Main Methods:

  • Review of AI/ML applications in digital phonocardiography for heart sound analysis.
  • Evaluation of large language models (LLMs) for medical knowledge assessment.
  • Discussion of integration strategies for AI/ML in clinical practice.

Main Results:

  • Digital PCG with AI/ML can objectively analyze heart sounds and predict clinical parameters.
  • LLMs demonstrate high accuracy (over 80%) in medical knowledge assessments.
  • Ongoing developments address challenges in AI/ML knowledge accuracy and consistency.

Conclusions:

  • AI/ML-driven digitalomics offers enhanced personalized cardiovascular risk assessment.
  • Digital PCG and AI text generators show significant potential in cardiovascular medicine.
  • Strategic implementation of validated AI/ML technologies can advance precision cardiovascular medicine.