Novel Approaches to Diagnosing Superficial Venous Insufficiency Using Artificial Intelligence
Tuesday, March 5, 2024
3:15 PM – 4:45 PM EST
Location: Foyer
Objective: Superficial venous insufficiency is a heterogeneous condition impacting the outermost vein system and can progress to deep vein pathology in late stages. The global disease burden is increasing due to aging populations, increased cardiovascular diseases and vascular risk factors. Screening and diagnosing this condition remains challenging, requiring physical examination findings, imaging studies and laboratory tests. However, the integration of artificial intelligence (AI) into the medical field presents new avenues for precise and efficient diagnosing. This article provides an overview of the AI’s potential in diagnosing superficial venous insufficiency and thrombosis, aiming to enhance medical practice.
Methods: We conducted a literature review using Cochrane Library and PubMed search engines, adhering to SANRA guidelines. Our research targeted articles concerning the use of AI in diagnosing superficial venous insufficiency. The search encompassed various types of publications including narrative reviews, systematic reviews, meta-analysis, clinical trials and randomized controlled trials, without language or country publication restrictions. The research was limited to resources published between 2019 and 2023. The following MeSH terms were used: “Artificial intelligence”, “superficial venous insufficiency”, “venous thrombosis”. Among the initial 160 identified matching results, only 17 articles met the inclusion criteria and were considered for further analysis.
Results: Literature provides substantial evidence linking Artificial Intelligence to the improvement of diagnostic capabilities in the realm of superficial vein pathology. The research brought evidence about Artificial Intelligence’ value in remote consultation, management of clinical data, and even genomics for vein pathology screening and prediction. Specifically, among the resources it was remarkable the possibility of incorporating risk factors and variables into the algorithm for vein pathology prediction.
Conclusions: Incorporation of Artificial Intelligence in vascular medicine has opened up novel scenarios for the screening, decision making and diagnosis of superficial vein insufficiency. Along the research it was demonstrated its applicability and efficiency in various clinical settings. Nonetheless, there is still a vast field of opportunities for Artificial Intelligence to complement physicians’ practice and enhance the diagnosis of lower vein pathology.
