Introduction:

Chronic venous insufficiency (CVI) is a prevalent condition with significant health and economic burdens. As the condition progresses, it can severely impact patients’ quality of life. Recent developments in Artificial Intelligence (AI) in healthcare offer promising solutions, providing tools that can enhance the accuracy of diagnosis, improve disease staging, and guide treatment decisions. This review aims to comprehensively synthesize and evaluate the role of AI techniques applicable to the management of CVI based on current evidence. 

Methods:

Adhering to 2020 PRISMA guidelines, we systematically searched Pubmed, Science Direct, CENTRAL, and Scopus for studies published in 2014–2024 which applied AI techniques in the management of CVI. We excluded studies that were case reports, case series, review articles, guidelines, or those that contained unpublished or incomplete data, or where the full text was not available in English or Indonesian. Analyses used descriptive statistics to summarize findings, emphasizing the reported statistical results. Risk-of-bias was assessed using the Prediction model Risk Of Bias Assessment Tool (PROBAST). 

Results:

Our review of 9 studies reported AI uses in forms of deep learning and machine learning, including deep convolutional neural networks, natural language processing, computer vision, fuzzy logic, logistic regression, and random forest which showed moderate to high accuracy or performance in CVI management, including diagnosis and prognosis. CVI severity, ulcer size and etiologies, as well as the risk of ulcer development could be predicted by the AI. The majority of the studies (88,9%) demonstrated a high or unclear risk of bias. AI has demonstrated significant potential in enhancing the management of CVI patients, particularly in diagnosis, prognosis, and decision-making support. 

Conclusion:

AI has shown significant potential in enhancing the management of CVI patients, particularly in diagnosis, prognosis, and decision-making support. However, further high-quality quantitative studies are needed to confirm its effectiveness.

Andrea Radyaputri is a medical doctor pursuing specialty degree in field of cardiac, thoracic and vascular surgery at Universitas Gadjah Mada, Yogyakarta, Indonesia. While undertaking the second semester of residency, she has published several publications related to cardiovascular, thoracic, as well as neuro-surgery, including a literature review and several reports of unique cases throughout the past 3 years. She has also been participating in medical science olympiads involving that focused on topics such as anatomy, physiology, microbiology, and immunology, paper presentations in several prestigious national conferences, as well as becoming a research assistant in fields of anesthesiology and cardiothoracovascular surgery.