Abstract
Lymphoma, a heterogeneous group of blood cancers, presents significant diagnostic and therapeutic challenges due to its complex subtypes and variable clinical outcomes. Artificial intelligence (AI) has emerged as a promising tool to enhance the accuracy and efficiency of lymphoma pathology. This review explores the potential of AI in lymphoma diagnosis, classification, prognosis prediction, and treatment planning, as well as addressing the challenges and future directions in this rapidly evolving field.
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