Dr. Mauro Giuffrè is a Postdoctoral Fellow in the Section of Digestive Diseases at Yale School of Medicine. After completing his Digestive Diseases fellowship at the University of Trieste and earning a Master’s in Biostatistics at the University of Padova, he is now finalizing a PhD in Applied Data Science and Artificial Intelligence in the Department of Mathematics at Trieste. He serves on the Artificial Intelligence Commission of the Italian Association for the Study of the Liver (AISF).
As a clinical informaticist and physician–scientist, Dr. Giuffrè has presented and published extensively at both national and major international conferences, developing and refining methodologies and best practices to improve Large Language Models and Generative Artificial Intelligence techniques to support clinical decision-making in hepatology. His research focuses particularly on developing robust evaluation frameworks for assessing the safety and reliability of Generative Artificial Intelligence models in high-stakes medical environments, as well as optimizing the interpretation of evidence-based medicine through the creation of an LLM-friendly version of clinical guidelines. He has pioneered methodologies for ranking and validating the performance of Generative Artificial Intelligence models against expert-level clinical knowledge, ensuring that automated systems meet the rigorous accuracy standards required for clinical practice. His work emphasizes human–algorithmic integration, uniting clinician expertise with explainable artificial intelligence and Large Language Models to deliver transparent, trustworthy decision support in hepatology. He has actively developed predictive models for non-invasive risk stratification in chronic liver disease and designs clinical decision support systems that seamlessly integrate these models into care pathways to enhance diagnostic accuracy and treatment planning.