VEITH Symposium Showcases Emerging AI Applications in Vascular Care Led by Veith and Dinc

NEW YORK, Nov. 20, 2025 /PRNewswire/ -- Frank J. Veith and Rasit Dinc presented new expert insights on the role of advancing artificial intelligence (AI) technologies in contemporary vascular medicine during a featured session at the 52nd annual VEITH Symposium. Their discussion outlined how emerging computational platforms may influence clinical decision-making, procedural planning, and long-term outcomes across endovascular care.

Delivered at one of the field's leading global forums, the session highlighted the growing importance of AI-enabled imaging, simulation, and digital workflow tools within vascular surgery and interventional practice. The VEITH Symposium, held in academic partnership with the Cleveland Clinic, continues to serve as a platform for introducing new advancements and shaping international perspectives on the future of vascular innovation.

A Global Platform for Vascular Innovation

The five-day meeting, known for its concise, rapid-fire presentations, draws thousands of vascular surgeons, interventional cardiologists, radiologists, and allied specialists from around the world. This year's program underscored a marked expansion in sessions dedicated to AI, digital workflow integration, intravascular imaging, and computational modeling, reflecting their rising impact on clinical practice.

Dinc, whose work on AI-enhanced intravascular imaging and endovascular planning has earned international attention, outlined how machine-learning algorithms and three-dimensional virtual modeling are beginning to optimize precision in complex vascular procedures.

AI as a Decision-Support Engine in Vascular Disease

In his remarks, Dinc emphasized that AI should be viewed as a decision-support engine rather than a replacement for clinical expertise. By integrating patient-specific imaging with computational simulation, he noted, clinicians can virtually test procedural scenarios before entering the operating room.

"Digitally evaluating potential treatment pathways in advance can reduce complication rates and improve procedural predictability, particularly in high-risk cases," Rasit Dinc stated.

He explained that AI-driven simulation platforms hold significant value for the management of aortic aneurysms, peripheral artery disease, and complex vascular lesions, where anatomy and pathology vary widely across patients. Machine-learning systems trained on extensive clinical datasets can compare thousands of analogous cases and propose strategies associated with optimal outcomes.

Ethics, Transparency, and Scientific Rigor at the Center of Adoption

Dinc also addressed the broader ecosystem required for the responsible implementation of medical AI. He highlighted four foundational pillars essential for progress:

• Algorithmic transparency and interpretability
• High-quality, representative datasets
• Robust ethical and legal frameworks
• Rigorous, prospective clinical validation

He underscored the necessity of multidisciplinary cooperation spanning engineering, medicine, data science, and law to ensure that digital systems enhance rather than complicate the delivery of vascular care.

Veith: Innovation Must Be Anchored in Evidence

In his commentary, Frank J. Veith reaffirmed vascular surgery's longstanding reputation for embracing technological innovation but cautioned that new tools must be supported by strong scientific evidence.

The session also explored the interplay between AI-enabled decision-support systems, advanced imaging modalities, telemedicine tools, and remote monitoring technologies. Jointly, these capabilities may help reduce disparities between major referral centers and peripheral or resource-limited environments.

Dinc concluded by emphasizing that a well-structured digital health infrastructure can expand access to expert-level vascular care, mitigate geographic inequities, and strengthen global standards in endovascular therapy.

Contact
Alex DuPont
VEITH Symposium
[email protected] 

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SOURCE VEITH Symposium