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The Narrative Review: Advancements in Heart Failure Diagnosis and Management using Artificial Intelligence: A New Era
Sunchandandeep Singh Brar1, Meenakshi Reddy Yathindra2, Juan Sebastian Arias Arango3
1Department of Internal Medicine, China Medical University, Shenyang, China.
Insights
Artificial Intelligence (AI) offers advanced solutions for managing Heart Failure (HF). AI improves diagnosis, risk assessment, and personalized treatment, leading to better patient outcomes and healthcare practices.
Area of Science:
- Cardiology
- Medical Informatics
- Artificial Intelligence
Background:
- Heart Failure (HF) is a growing global health concern with increasing prevalence.
- Current HF management faces challenges in diagnosis, progression, readmission rates, and therapeutic interventions.
- Artificial Intelligence (AI) presents promising solutions to enhance HF care.
Purpose of the Study:
- To review the current progress and future potential of AI in Heart Failure management.
- To highlight how AI techniques can improve clinical decision-making and patient outcomes.
- To identify areas for further development in AI for HF treatment.
Main Methods:
- Review of current AI applications in Heart Failure.
- Analysis of machine learning and deep learning techniques for diagnosis and risk prediction.
- Exploration of AI's role in personalized treatment strategies.
Main Results:
- AI enhances diagnostic accuracy through analysis of medical imaging and electrocardiograms.
- AI algorithms enable precise risk stratification for personalized treatment plans.
- AI facilitates early problem identification and selection of appropriate therapies, improving patient outcomes.
Conclusions:
- AI is crucial for improving Heart Failure management, offering enhanced decision-making and patient care.
- Further advancements in data integration, predictive accuracy, and ethical considerations are needed.
- Continued AI development is essential for optimizing Heart Failure treatment and patient outcomes.
Abstract:
Heart Failure (HF) is a prevalent medical illness worldwide that affects millions and is a substantial economic burden. Its epidemiological impact is on the rise due to factors such as the ageing of the population, increasing rates of diabetes and hypertension, and better survival post-myocardial infarction. Some limitations in HF management include diagnostic challenges, sudden progression of the disease, and rising rates of readmission. Continuous monitoring and limited therapeutic interventions add further complexity to care. Artificial Intelligence(AI) is essential in health care and has provided solutions for improving HF management. Techniques like machine learning and deep learning enhance clinical decision-making and patient care. AI helps physicians diagnose HF more precisely through the analysis of imaging and electrocardiograms. Additionally, the patients' risk is calculated using various AI algorithms to develop personalized treatments for each individual. AI will help healthcare providers identify problems early and select appropriate therapies, leading to better outcomes. Further areas for improvement include enhanced data integration, predictive accuracy, patient engagement, data privacy and ethics, as well as integration with clinical workflows. AI technologies will continue to evolve in managing and treating HF; ongoing exploration and development are crucial for its optimization. This review outlines the current progress and potential of AI in the future to ensure better patient care and healthcare practices.
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