Artificial Intelligence Evidence-Based Current Status and Potential for Lower Limb Vascular Management.

Area of Science:

• Vascular Medicine
• Medical Informatics
• Artificial Intelligence

Background:

• Consultation prioritization is crucial for healthcare management, with digital medicine and AI offering significant improvements.
• Remote consultations are essential, especially highlighted by the pandemic and for underserved rural populations.
• Artificial intelligence (AI), utilizing machine learning and neural networks, simulates human intellectual behavior for minimal intervention.

Purpose of the Study:

• To review the current data on the implementation of AI in the diagnostics and care of arterial and venous diseases.
• To explore AI's potential in improving vascular disease diagnostics and management.

Main Methods:

• Narrative review of available literature on AI applications in vascular disease.
• Analysis of AI's role in diagnostic algorithms and personalized treatments across various medical fields.
• Examination of AI in analyzing imaging data (MRI, ultrasound, CT angiography) for vascular conditions.

Main Results:

• AI demonstrates potential in diagnosing peripheral artery disease, cerebrovascular disease, deep vein thrombosis, and pulmonary embolism.
• Automatic AI methods can detect chronic venous disease presence and clinical class.
• Current data on AI implementation in vascular diseases remains limited.

Conclusions:

• AI shows promise for enhancing vascular disease diagnostics and management, including remote consultations.
• Further research and data are needed to fully realize AI's potential in vascular medicine.
• AI can assist specialists in analyzing complex imaging data for accurate vascular diagnoses.