Abstract
Personalized medicine in hematology requires extensive real-world and comprehensive data, including clinical and genomic information. However, integrating, processing and managing such complex data layers in large populations presents significant challenges. Development of patient-tailored models by Artificial Intelligence (AI), known as Digital Twins (DT) offers a novel approach to precision medicine. DT are virtual representations of patients created from multimodal information that can be used to improve diagnosis, prognosis and treatment outcome, improving clinical decision-making. This project aims to advance research by using AI to develop a DT platform for personalized medicine in hematology, with myelodysplastic syndromes (MDS) as case study. MDS are hematological diseases with high clinical and genomic heterogeneity, presenting a challenging scenario for new technologies implementation.