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Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
Published on: February 13, 2021
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Artificial intelligence and heart failure: A state-of-the-art review
Muhammad Shahzeb Khan1, Muhammad Sameer Arshad2, Stephen J Greene1,3
1Division of Cardiology, Duke University School of Medicine, Durham, NC, USA.
European Journal of Heart Failure
|August 10, 2023
Summary
Artificial intelligence (AI) offers advanced risk prediction for heart failure (HF) patients, improving early diagnosis and management. AI algorithms can synthesize complex data, aiding physicians in making timely, informed decisions for better heart failure care.
Area of Science:
- Cardiology
- Artificial Intelligence
- Health Informatics
Background:
- Heart failure (HF) affects over 60 million globally, presenting complex challenges in risk stratification and management.
- Despite advancements, issues like residual risk and understanding HF with preserved ejection fraction persist.
- Integrating vast, disparate patient data for effective HF care remains a significant hurdle.
Purpose of the Study:
- To review artificial intelligence (AI) algorithms for early HF diagnosis, phenotyping HF with preserved ejection fraction, and disease severity stratification.
- To discuss challenges in the clinical deployment of AI in HF care.
- To explore future directions for AI-driven improvements in HF management.
Main Methods:
- Review of existing literature on AI algorithms applied to heart failure.
- Analysis of AI's capabilities in data integration and synthesis for clinical decision support.
- Discussion of challenges and future prospects for AI in HF.
Main Results:
- AI algorithms show potential for superior predictive ability over traditional methods in HF risk stratification.
- AI can facilitate clinical decision-making, optimize treatment allocation, predict adverse outcomes, and enable early detection of worsening HF.
- AI aids in early HF diagnosis, phenotyping HF with preserved ejection fraction, and stratifying disease severity.
Conclusions:
- AI holds significant promise for transforming heart failure care by enhancing diagnostic accuracy and treatment personalization.
- Overcoming challenges in AI deployment is crucial for realizing its full potential in improving patient outcomes.
- Future development of novel AI algorithms is essential for advancing the management of heart failure.
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