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<p>Vascular disease (VD) is a medical condition that adversely affects the blood vessels. Peripheral Artery Disease (PAD), a significant form of VD, is a major global health concern. In developing countries such as Bangladesh, VDs often remain undiagnosed and untreated until reaching critical stages. Artificial Intelligence (AI) based methods have potential for early detection and improved treatment guidelines. This paper narratively reviews both the clinical and the AI aspects of VD, emphasizing PAD, by examining recent studies on clinical diagnostic methods, treatment strategies and clinical outcomes, highlighting AI-driven research, machine learning (ML) algorithms contributing to disease management. Existing research on VDs, addresses their epidemiology, diagnosis, treatment, prevalence and morbidity, and mortality. It shows the need for more context-sensitive treatment data, age-specific studies, better access to technology, precise treatment goals, and rigorous diagnostic methodologies. Several works have explored AI algorithms to analyze diverse data sources - such as electronic health records (EHR), radiology images, genetic data and pulse wave signals for PAD detection, achieving accuracy exceeding 94%. AI is also being investigated for the prediction and management of PAD, atherosclerosis, venous thromboembolism, aneurysms, blood clots, etc. However, significant challenges in this sector include a lack of datasets, data imbalance, a lack of clear legal and regulatory frameworks, and the need for clinically validated models capable of handling diagnosis, risk assessment, and treatment planning. This review explores the potential of AI in combating VDs, providing insights into current approaches for using these technologies in effective detection and management.</p>

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A Review of the Application of Artificial Intelligence in Vascular Disease with a Particular Focus on Peripheral Artery Disease

  • 期刊论文

  • 发表日期：

    2026年5月14日

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  • Md Raisul Islam,
  • Mashrukh Zaman,
  • Syed Ahmmed,
  • Riad Hassan,
  • M. Rubaiyat Hossain Mondal,
  • Abul Hasan Muhammad Bashar,
  • Sheikh Iqbal Ahamed

摘要

Vascular disease (VD) is a medical condition that adversely affects the blood vessels. Peripheral Artery Disease (PAD), a significant form of VD, is a major global health concern. In developing countries such as Bangladesh, VDs often remain undiagnosed and untreated until reaching critical stages. Artificial Intelligence (AI) based methods have potential for early detection and improved treatment guidelines. This paper narratively reviews both the clinical and the AI aspects of VD, emphasizing PAD, by examining recent studies on clinical diagnostic methods, treatment strategies and clinical outcomes, highlighting AI-driven research, machine learning (ML) algorithms contributing to disease management. Existing research on VDs, addresses their epidemiology, diagnosis, treatment, prevalence and morbidity, and mortality. It shows the need for more context-sensitive treatment data, age-specific studies, better access to technology, precise treatment goals, and rigorous diagnostic methodologies. Several works have explored AI algorithms to analyze diverse data sources - such as electronic health records (EHR), radiology images, genetic data and pulse wave signals for PAD detection, achieving accuracy exceeding 94%. AI is also being investigated for the prediction and management of PAD, atherosclerosis, venous thromboembolism, aneurysms, blood clots, etc. However, significant challenges in this sector include a lack of datasets, data imbalance, a lack of clear legal and regulatory frameworks, and the need for clinically validated models capable of handling diagnosis, risk assessment, and treatment planning. This review explores the potential of AI in combating VDs, providing insights into current approaches for using these technologies in effective detection and management.