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The Role of Artificial Intelligence in the Prediction, Diagnosis, and Management of Cardiovascular Diseases: A
Mohammed Farooque W Shaikh1, Murtaza S Mama2, Sri Harika Proddaturi3
1Internal Medicine, Dow University of Health Sciences, Dow International Medical College, Karachi, PAK.
Insights
Artificial Intelligence (AI) offers transformative potential for cardiovascular disease (CVD) management by enhancing diagnostics and treatment strategies. Overcoming implementation challenges is crucial for integrating AI into clinical practice and improving patient outcomes.
Area of Science:
- Cardiology
- Medical Informatics
- Artificial Intelligence
Background:
- Cardiovascular diseases (CVDs) are the leading cause of global mortality, with increasing prevalence and premature deaths.
- Early detection and management of CVDs are complex due to disease dynamics and large patient populations.
Purpose of the Study:
- To explore the application of Artificial Intelligence (AI) in cardiovascular care.
- To review the limitations of current AI implementation in cardiology.
- To discuss future integration of AI for improved patient outcomes.
Main Methods:
- Review of recent advancements in AI, machine learning (ML), and deep learning technologies for analyzing cardiovascular data.
- Examination of AI-driven decision support systems and automated image assessment tools.
- Analysis of challenges hindering AI implementation in clinical settings.
Main Results:
- AI technologies demonstrate potential to improve diagnostic accuracy and optimize treatment strategies in cardiovascular care.
- AI enables personalized medicine through customized decision support and automated assessments.
- Significant obstacles to AI implementation include regulatory, privacy, validation, interoperability, and clinician acceptance issues.
Conclusions:
- Despite implementation hurdles, AI holds significant promise for advancing cardiovascular medicine.
- Further research and development are essential to overcome current limitations.
- Successful integration of AI is key to achieving better patient outcomes in cardiovascular disease management.
Abstract:
Cardiovascular diseases (CVDs) remain the leading global cause of mortality, and a high prevalence of cardiac conditions, including premature deaths, have increased from decades until today. However, early detection and management of these conditions are challenging, given their complexity, the scale of affected populations, the dynamic nature of the disease process, and the treatment approach. The transformative potential is being brought by Artificial Intelligence (AI), specifically machine learning (ML) and deep learning technologies, to analyze massive datasets, improve diagnostic accuracy, and optimize treatment strategy. The recent advancements in such AI-based frameworks as the personalization of decision-making support systems for customized medicine automated image assessments drastically increase the precision and efficiency of healthcare professionals. However, implementing AI is widely clogged with obstacles, including regulatory, privacy, and validation across populations. Additionally, despite the desire to incorporate AI into clinical routines, there is no shortage of concern about interoperability and clinician acceptance of the system. Despite these challenges, further research and development are essential for overcoming these hurdles. This review explores the use of AI in cardiovascular care, its limitations for current use, and future integration toward better patient outcomes.
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