Methoden der künstlichen Intelligenz in der vaskulären Medizin: Status quo und Ausblick am Beispiel des AAAs

Background: Artificial intelligence (AI) methods enjoy widespread use in an ever-increasing number of areas. In particular, the use of AI in medicine has seen incremental growth in recent years. Objective: To what extent are AI methods being used in vascular medicine at present? What are potential clinical applications? What are the challenges? Material and methods: Current applications of AI methods in medicine are presented on the basis of a literature search, existing AI approaches and possibilities for the application in the field of vascular surgery are discussed. By means of a current research topic, namely estimation of the risk of rupture in abdominal aortic aneurysms (AAA), the use and interplay of different AI methods are presented. Results: In the field of vascular surgery AI methods are still underrepresented. As evidenced by the example of AAA there is a high potential for application in vascular medicine. Conclusion: While promising, the AI methods and models suffer from a lack of interpretability, i.e. they are limited in their ability to provide insights as to the causal mechanisms dictating an observed phenomenon. Moreover, the development of accurate and diagnostically conclusive AI models necessitates large medical datasets. Due to data privacy concerns, the sharing of medical data poses a complex legal problem, particularly in Germany, and represents another barrier for expanding the use of AI methods.