Does Artificial Intelligence Bring New Insights in Diagnosing Phlebological Diseases?-A Systematic Review

Area of Science:

• Medical Imaging
• Artificial Intelligence in Medicine
• Vascular Diagnostics

Background:

• Artificial intelligence (AI) is revolutionizing medical diagnostics, particularly for complex conditions.
• Venous pathologies, including chronic venous disease (CVD), venous reflux, and deep venous thrombosis (DVT), present diagnostic challenges.
• AI offers potential for improved accuracy, workflow efficiency, and clinical decision-making in venous diagnostics.

Purpose of the Study:

• To evaluate the efficacy and feasibility of AI algorithms in diagnosing venous diseases.
• To explore the impact of AI on clinical practice for venous pathology diagnosis.

Main Methods:

• A comprehensive literature review of AI applications in venous pathology diagnostics.
• Searched multiple electronic databases: MEDLINE/PubMed, Web of Science, Scopus, Embase, ResearchGate, and Google Scholar.
• Analyzed findings from nine major studies involving over 1000 patients.

Main Results:

• AI algorithms demonstrated diagnostic accuracy exceeding 90% for venous pathologies.
• AI significantly reduced inter-observer variability and improved consistency in interpreting ultrasonographic images.
• AI accelerated diagnostic workflows, decreasing image analysis time by over 50%, and detected subtle abnormalities.
• AI identified minor venous reflux and early-stage thrombi often missed in manual evaluations.

Conclusions:

• AI is a transformative innovation for diagnosing and managing venous diseases.
• AI enhances diagnostic accuracy, streamlines workflows, and enables personalized patient care.
• Future developments include AI integration into ultrasound devices, multimodal data fusion, predictive analytics for disease progression, and large-scale dataset construction.