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Artificial intelligence in preventive cardiology.

Adham El Sherbini1, Robert S Rosenson2, Mahmoud Al Rifai3

  • 1Faculty of Health Sciences, Queen's University, Kingston, ON, Canada.

Progress in Cardiovascular Diseases
|March 9, 2024
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) can enhance preventive cardiology by screening and monitoring cardiovascular disease (CVD) risk factors. Further clinical trials are needed to fully evaluate AI

Keywords:
AlcoholArtificial intelligenceBlood pressureDyslipidemiaMachine learningMental healthNutritionPhysical activityPreventive cardiologyRecreational drugsSleep hygieneSmokingWeight loss

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Area of Science:

  • Cardiology
  • Artificial Intelligence
  • Preventive Medicine

Background:

  • Preventive cardiology focuses on mitigating cardiovascular disease (CVD) risk factors.
  • Artificial intelligence (AI) aims to replicate human intelligence in machines.
  • Integrating AI into preventive cardiology offers potential for novel interventions and clinician tools.

Purpose of the Study:

  • To review current applications, potential benefits, and limitations of AI in CVD prevention.
  • To explore AI's role in managing key CVD risk factors.
  • To highlight the need for further clinical validation of AI in this field.

Main Methods:

  • Literature review of AI applications in preventive cardiology.
  • Analysis of AI's impact on risk factor management (nutrition, weight, activity, sleep, etc.).
  • Discussion of AI's potential for screening, detection, and monitoring.

Main Results:

  • AI has been investigated across various CVD risk factors, showing potential for screening and monitoring.
  • AI tools can assist clinicians in preventive cardiology.
  • Current literature requires more clinical trials to validate AI's effectiveness.

Conclusions:

  • AI demonstrates significant potential to advance primary and secondary CVD prevention.
  • AI can aid in managing lifestyle and physiological risk factors.
  • Future research and clinical trials are crucial to realize AI's full capabilities in preventive cardiology.