人工智能在淋巴瘤诊断、基因预测和预后评估中的应用  

Advances in artificial intelligence applications in lymphoma diagnosis,gene prediction,and prognostic assessment

作　　者：罗丹 曲桂梅[2] LUO Dan;QU Guimei(Second School of Clinical Medicine,Binzhou Medical University,Yantai Shandong 264003;Department of Pathology,Yantai Yuhuangding Hospital Affiliated to Qingdao University,Yantai Shandong 264000,China)

机构地区：[1]滨州医学院第二临床医学院,山东烟台264003 [2]青岛大学附属烟台毓璜顶医院病理科,山东烟台264000

出　　处：《临床与病理杂志》2024年第7期1027-1032,共6页Journal of Clinical and Pathological Research

摘　　要：淋巴瘤是起源于淋巴造血组织的恶性肿瘤,在临床表现、细胞形态、治疗反应及预后等方面均表现出高度异质性。人工智能(artificial intelligence,AI)是对智能的模拟,其使用数据、规则和编程信息来进行预测。近年来,AI技术越来越多地应用于诊断病理学,建立在AI基础上的深度学习在淋巴瘤研究中也得到了广泛应用。AI与数字病理学的结合将淋巴瘤预测准确性提升到新的高度,包括诊断、基因预测和预后评估等方面,这将有助于辅助病理医师进行淋巴瘤病理诊断,从而为淋巴瘤精准治疗提供更快速、更客观的依据。Lymphoma,a malignant tumor originating from lymphohematopoietic tissue,exhibits high heterogeneity in clinical presentation,cell morphology,treatment response,and prognosis.Artificial intelligence(AI)is a simulation of intelligence that utilizes data,rules,and programming information to make predictions.In recent years,AI technologies have been increasingly applied to diagnostic pathology,with deep learning based on AI seeing broad application in lymphoma research.The integration of AI with digital pathology has elevated the accuracy of lymphoma prediction to new levels,particularly in diagnosis,gene prediction,and prognostic assessment.This progress aids pathologists in making pathological diagnoses of lymphoma,thereby providing a faster and more objective basis for precise treatment of lymphoma.

关 键 词：人工智能 淋巴瘤 数字病理学 深度学习 基因预测 

分 类 号：R733.1[医药卫生—肿瘤]