DIGITAL HEALTH TECHNOLOGIES FOR PREDICTING CARDIOVASCULAR RISK AND DISEASE PROGRESSION

Authors

  • Maxsudov Valijon Gafurjonovich
  • Arzikulov Fazliddin Faxriddin o‘g‘li Associate Professor, Department of Biomedical Engineering, Informatics and Biophysics, Tashkent State Medical University

DOI:

https://doi.org/10.17605/

Keywords:

Artificial intelligence, cardiovascular diseases, diagnostic tools, machine learning, digital health, risk prediction, clinical decision-making, personalized medicine.

Abstract

Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, necessitating the development of accurate and scalable prognostic tools. The emergence of digital technologies-including electronic health records (EHRs), wearable sensors, mobile health applications, and advanced artificial intelligence (AI) systems-has transformed the landscape of cardiovascular risk prediction and disease management. These technologies enable continuous monitoring, early detection of pathological changes, and personalized prognostic assessment based on large-scale, real-world data.

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Published

2025-03-31

Issue

Vol. 6 No. 3 (2025): wos

Section

Articles

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