Miao Shen,1,2 Zhinong Jiang1 

1Department of Pathology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou City, Zhejiang Province, 310000, People’s Republic of China; 2Department of Pathology, Deqing People’s Hospital, Huzhou City, Zhejiang Province, 313200, People’s Republic of China

Correspondence: Zhinong Jiang, Department of Pathology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, No. 3 Qingchun East Road, Shangcheng District, Hangzhou City, Zhejiang Province, 310000, People’s Republic of China, Tel +86 15105729672, Email jiangzn2003@163.com

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.

Keywords: artificial intelligence, machine learning, deep learning, lymphoma, digital pathology