SESSION DESCRIPTION
This session highlights the transition of AI from diagnostic innovation to clinical decision support and personalized patient management. Presentations demonstrate how AI can predict treatment-related toxicities and complications, identify cardiovascular and bleeding risks, enhance MRD assessment, automate diagnostic triage, and improve disease risk stratification. Together, these studies illustrate the emerging role of AI in anticipating clinical outcomes, guiding therapeutic decisions, and enabling more precise, individualized care in hematologic malignancies.
KEYWORDS
Technology and Procedures, Assays, Imaging, Molecular Testing, Pathology, Bioinformatics, Emerging Technologies, Treatment Considerations, Biological Therapies, (CAR)-T Cell Therapies, Adverse Events, Artificial Intelligence (AI), Computer Vision, Deep Learning, Machine Learning, Natural Language Processing, Diseases, Bleeding and Clotting, Thromboembolism, Thrombotic Disorders, Lymphoid Malignancies, Lymphoid Leukemias, Lymphomas, Plasma Cell Disorders, Measurable Residual Disease, ALL, Non-Hodgkin Lymphoma, B Cell Lymphoma, Aggressive Lymphoma, Research, Translational Research, Clinical Research, Real-World Evidence