Assessment of Artificial Intelligence Algorithms for ROTEM

The goal of this observational validation study is to evaluate whether artificial intelligence (AI) models can accurately interpret ROTEM (Rotational Thromboelastometry) data and provide appropriate treatment recommendations in adult patients undergoing elective cardiac or liver transplantation surgery. The main questions it aims to answer are: Can AI models (e.g., ChatGPT and Gemini ) accurately determine whether treatment is indicated based on ROTEM parameters? Can AI models correctly identify the type of coagulopathy (e.g., fibrinogen deficiency, platelet dysfunction)? Are the treatment recommendations from AI models concordant with expert clinical consensus? Researchers will compare the decisions made by AI models to a gold standard expert panel to see if AI models can match or approximate expert-level decision-making in interpreting ROTEM outputs. Participants will: Undergo elective cardiac or liver transplant surgery. Have standard ROTEM tests performed intraoperatively. Have their anonymized ROTEM data reviewed independently by: A panel of 3 clinical experts. AI models (ChatGPT and Gemini) using standardized prompts and ROTEM interpretation guidelines.