Virtual Multidisciplinary Teams: Exploring ChatGPT’s Application in the Diagnosis and Treatment of Complex Vascular Syndromes

Abstract

Sturge-Weber syndrome (SWS) and Klippel-Trenaunay syndrome (KTS) are complex vascular malformation syndromes requiring multidisciplinary team (MDT) approaches for diagnosis and treatment. Traditional MDTs face challenges such as scheduling conflicts, geographical barriers, and inefficient communication, particularly in remote areas. This study explores the use of ChatGPTo1, an AI language model capable of complex reasoning, to simulate MDT decision-making for these conditions. We analyzed clinical data, imaging, and genetic information for two SWS and two KTS patients, using ChatGPTo1 to generate diagnostic and treatment recommendations. These were compared to actual MDT outcomes. ChatGPTo1 demonstrated strong diagnostic integration, though discrepancies arose in specific genetic details. Despite limitations, the model showed promise in offering personalized treatment recommendations, particularly in the context of photodynamic therapy. This research provides early evidence of AI’s role in supporting MDTs for complex diseases and offers insights into the future of cross-disciplinary AI collaboration in healthcare.

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