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Review
. 2025 Mar 28;17(3):e81332.
doi: 10.7759/cureus.81332. eCollection 2025 Mar.

The Role of Artificial Intelligence in the Prediction, Diagnosis, and Management of Cardiovascular Diseases: A Narrative Review

Mohammed Farooque W Shaikh  1 , Murtaza S Mama  2 , Sri Harika Proddaturi  3 , Juan Vidal  4 , Pritika Gnanasekaran  5 , Mekala S Kumar  6 , Cleve J Clarke  7 , Kalva S Reddy  6 , Hasiya M Bello  8 , Naama Raquib  9 , Zoya Morani  10
Affiliations
Review

The Role of Artificial Intelligence in the Prediction, Diagnosis, and Management of Cardiovascular Diseases: A Narrative Review

Mohammed Farooque W Shaikh et al. Cureus. .

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.

Keywords: artificial intelligence in cardiology; cardiovascular disease diagnosis; cardiovascular diseases (cvds); machine learning in healthcare; personalized medicine.

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Conflict of interest statement

Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work.

Figures

Figure 1
Figure 1. Role of artificial intelligence in cardiovascular diseases.
Reproduced under CC BY 4.0. Publisher BMC [19].
Figure 2
Figure 2. The various types and patterns of ROC curves comparing the true positive and false positive rates for coronary artery classification are shown in five different images: (A) DenseNet201, (B) EfficientNet-B0, (C) MobileNet-v2, (D) ResNet101, and (E) Xception.
Reproduced under CC BY 4.0. Publisher MDPI [60].
Figure 3
Figure 3. (A, B) Echocardiography AI applications
Reproduced under CC BY 4.0. Publisher MDPI [65].
See this image and copyright information in PMC

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