Artificial Intelligence in vascular immunology: transforming diagnosis, risk classification, and therapeutic decision-making processes

Artificial intelligence (AI) is rapidly redefining the field of vascular immunology, an area that investigates immune and inflammatory mechanisms underlying vascular diseases such as atherosclerosis, aortic aneurysms, stroke, venous thromboembolism, and vasculitis. Despite significant progress in unraveling the role of the immune system in vascular pathology, diagnostic precision, risk assessment, and effective treatment selection remain challenging. Recent advancements in machine learning, deep learning, and natural language processing have opened new possibilities for integrating complex biological, clinical, and imaging data, thus enhancing our understanding and management of immune-mediated vascular disorders. Although initial studies demonstrate the promise of AI-driven biomarker identification and innovative clinical decision support, the translation of these findings into everyday clinical practice remains limited by validation standards, regulatory oversight, and the need for more robust interdisciplinary approaches.This Research Topic aims to foster the integration of artificial intelligence into vascular immunology, focusing specifically on decoding vascular inflammation, to drive innovations in diagnosis, risk classification, and therapeutic decision-making. The central goal is to identify, evaluate, and promote AI-based strategies that enhance prediction, stratification, and personalized treatment of immune-mediated vascular diseases. This includes investigating the clinical utility of novel AI models, addressing translational challenges, and generating evidence for improved patient outcomes. Contributors are encouraged to present original research, comprehensive reviews, methodological advances, and expert perspectives that bridge data science, immunology, and clinical medicine.This Research Topic prioritizes studies that combine AI-based predictions with robust biological or experimental validation and offer mechanistic insight into vascular inflammation. Submissions incorporating independent, multicenter or prospective validation, comparisons with established clinical models, and clinically meaningful endpoints are especially encouraged. Transparent reporting of model performance, bias, explainability, and generalizability is considered essential to ensure scientific rigor. Adherence to standardized methodologies, external benchmarking, and open data and code availability will be valued, as will explicit demonstration of whether AI-driven approaches improve patient outcomes or therapeutic decisions beyond conventional methods — all of which are central to maximizing the reproducibility, translational relevance, and overall impact of this collection.To gather further insights into the application and boundaries of AI in vascular immunology, we welcome articles that address, but are not limited to, the following themes:o AI-driven discovery of vascular inflammatory biomarkers through multi-omics integration and predictive modeling.o Clinical decision support systems for risk stratification and treatment selection incorporating immunological and inflammatory data.o Deep learning in vascular imaging to detect, monitor, and quantify vessel wall inflammation and plaque vulnerability.o Computational models to predict patient-specific responses to immunomodulatory and anti-inflammatory therapies in vascular diseases.o AI-assisted prediction of immune-mediated and inflammatory complications in vascular interventions and device selection.o Regulatory pathways, validation standards, and ethical challenges in clinical AI models implementation focused on inflammatory disease activity.o Translational pathways to accelerate the adoption of AI tools from vascular inflammation research to bedside clinical practice.Please note that manuscripts without a clear connection to immunology are not suitable for publication in this journal. Also, manuscripts without a experimental validation are also not considered for publication in this journal.Please also note that Dr. Nurittin Ardıç is the medical director of Invamed RD Global, a private medical device company; and serves as a volunteer consultant for Med-International UK Health Agency Ltd. where he receives no salary, equity, or financial compensation related to this role. This activity is not related to the subject matter of the present Research Topic. Also, Dr. Rasit Dinç serves as President of Invamed RD Global, and may hold intellectual property related to medical technologies. These interests are disclosed in the interest of transparency and are not directly related to the subject matter of the present Research Topic. Topic editors: Nurittin Ardic, Sarajo Mohanta, Patrick De Boever Source: https://www.frontiersin.org/research-topics/83174/artificial-intelligence-in-vascular-immunology-transforming-diagnosis-risk-classification-and-therapeutic-decision-making-processes