Cihan Ay and Colleagues on Large Language Models VS Thrombosis Experts
International Society on Thrombosis and Haemostasis (ISTH) shared on LinkedIn:
”AI meets thrombosis expertise
A new international study led in part by Cihan Ay, ISTH member and researcher at Medical University of Vienna, reveals that artificial intelligence (AI) language models can sometimes provide better answers than experts when educating patients about venous thromboembolism (VTE).
In complex clinical decision-making, the study found that AI recommendations were often on par with thrombosis specialists, a promising insight into the future of medical education and support tools.
Published in the Journal of Thrombosis and Haemostasis (JTH), the leading journal of the ISTH.
Learn more here.
Read the article here.”
Read the full article in JTH.
Article: Large language models versus thrombosis experts: A comparative study on patient education and clinical decision-making in venous thromboembolism
Authors: Nikola Vladic, Stephan Nopp, Ingrid Pabinger, Walter Ageno, Jean M. Connors, Sabine Eichinger, Cihan Ay, on behalf of the ClotGPT study group

Stay updated on all scientific advances in the field of thrombosis with Hemostasis Today.
-
Aug 30, 2026, 17:13J. Meireles-Brandao: Hypertension, Inflammation and Lipoprotein Disease
-
Aug 30, 2026, 17:10Hugh Nguyen: Leading the New Era of Blood Services Across Asia Pacific
-
Aug 30, 2026, 17:09Transforming Childhood Through Access to Hemophilia Treatment – World Federation of Hemophilia
-
Aug 30, 2026, 17:07Raj Bharath: Connecting Clinicians and Researchers to Advance Transfusion Medicine
-
Aug 30, 2026, 17:04Rana Al Hrout: Free FRCPath Haematology Part 1 Exam Preparation Session
-
Aug 30, 2026, 17:02David McGlasson: A 2020 Article Reaches 8,000 Reads
-
Aug 30, 2026, 16:18Tushar Namdeo: Platelets in Different Diseases
-
Aug 30, 2026, 16:16Fatima Zafar: Anaemia – Why This “Common” Condition Should Never Be Ignored
-
Aug 30, 2026, 16:13Umeshkumar C.: Evaluating Scoring Systems and Biomarkers for DIC in Critically Ill Patients