Artificial intelligence-based predictive models in vascular diseases

Area of Science:

• Cardiovascular Medicine
• Medical Informatics
• Artificial Intelligence

Background:

• Cardiovascular diseases remain a leading cause of global morbidity and mortality.
• Advances in personalized medicine require improved tools for individual prognosis prediction.
• Artificial intelligence (AI) and machine learning (ML) offer novel approaches to analyze complex health data.

Purpose of the Study:

• To review the application of AI-based prediction models in vascular diseases.
• To focus on aortic aneurysm, lower extremity arterial disease, and carotid stenosis.
• To discuss the potential of AI in advancing precision medicine for vascular conditions.

Main Methods:

• Literature review of AI and machine learning applications in vascular disease prediction.
• Analysis of studies focusing on aortic aneurysm, lower extremity arterial disease, and carotid stenosis.
• Discussion of challenges in integrating AI predictive models into clinical practice.

Main Results:

• AI, particularly ML, can identify complex patterns in health data for cardiovascular medicine.
• AI models show potential for predicting outcomes in specific vascular diseases.
• The review highlights the benefits of AI for personalized and precision medicine approaches.

Conclusions:

• AI-based prediction models hold significant promise for improving patient outcomes in vascular diseases.
• Further development is needed to overcome challenges for widespread clinical adoption of AI in vascular medicine.
• AI can facilitate the transition towards precision medicine in the management of vascular conditions.