Exploring the Potential of AI and Augmented Reality in Cardiovascular Disease Management: A Narrative Review

Aadil Mahmood Khan; Arlette Villalobos; Akhil Dhanjibhai Kakadiya; Harleen Kaur; Sara Tabassum; Ansari Maha Faisal; Rutyika Pardeshi; Dhavan Shah; Sarath Chandra Ponnada; Krish Patel

doi:10.2174/011573403X391863251015111807

Exploring the Potential of AI and Augmented Reality in Cardiovascular Disease Management: A Narrative Review

Curr Cardiol Rev. 2026 Jan 7. doi: 10.2174/011573403X391863251015111807. Online ahead of print.

Authors

Affiliations

¹ OSF Saint Francis Medical Centre, Peoria, Illinois, USA.
² Ponce Health Sciences University, USA.
³ GMERS Medical College & Hospital, Sola, Ahmedabad, India.
⁴ Government Medical College, Patiala, Patiala, India.
⁵ Dr. V.R.K Women's Medical College, Telangana, Aziz Nagar, India.
⁶ Danylo Halytsky Lviv National Medical University (Ukraine), Ukraine, Lviv, India.
⁷ GCS Medical College, Hospital and Research Center, Ahmedabad, Ahmedabad, India.
⁸ B.J Medical College, Ahmedabad, India.
⁹ Great Eastern Medical School and Hospital, Srikakulam, Srikakulam, India.
¹⁰ Government Medical College, Surat, India.

PMID: 41510734
DOI: 10.2174/011573403X391863251015111807

Abstract

Introduction: Cardiovascular diseases remain a leading cause of morbidity and mortality worldwide, with their rising incidence demanding a shift toward more personalized treatment approaches. Artificial intelligence (AI) and augmented reality (AR) are two newly evolving technologies that have found extensive usage in the field of cardiovascular medicine and surgery. AI-based models involve machine learning and deep learning neural networks. These primarily form the basis of prediction models, allowing the prediction of risk, survival, and risk stratification of patients.

Methods: A literature search was conducted using PubMed and Google Scholar, and it included studies published between 2003 and 2024. Articles were selected based on clinical relevance and applicability to cardiovascular disease management using artificial intelligence (AI) and AR. Keywords used included "cardiovascular disease," "artificial intelligence," "augmented reality," "diagnostic imaging," and "risk prediction." Studies were screened manually for inclusion based on the title and abstract review, followed by full-text evaluation for relevance and quality.

Results: This narrative review highlights how artificial intelligence (AI) and augmented reality (AR) are increasingly being applied in cardiovascular disease management. Despite recent studies, there remains a lack of proper evaluation of these models' efficacy, and therefore multiple large-scale trials are needed.

Discussion: Networks such as Convolutional Neural Networks (CNNs) and Natural Language Processing (NLP) have been used to improve image interpretation and documentation processes.

Conclusion: Further and larger studies are needed to test the efficacy and safety of these models. This narrative review summarizes recent findings in AI and AR and offers perspectives on future research.

Keywords: Artificial intelligence; augmented reality; cardiovascular disease; cardiovascular disease management.; prediction models; risk stratification.