深度学习辅助病理诊断领域的研究进展  

Research progress in the field of deep learning assisted pathological diagnosis

作　　者：王超[1,2] 郭英 崔磊 闫庆国[1,2] WANG Chao;GUO Ying;CUI Lei;YAN Qingguo(Department of Pathology,Medical College of Northwest University,Shaanxi Xi'an 710069,China;Key Laboratory of Resource Biology and Biotechnology in Western China,Ministry of Education,School of Medicine,Northwest University,Shaanxi Xi'an 710069,China;Department of Pathology,Xi'an Daxing Hospital,Shaanxi Xi'an 710003,China;Yan'an University,Shaanxi Yan'an 716000,China;Northwest University School of Information Science and Technology,Shaanxi Xi'an 710127,China.)

机构地区：[1]西北大学医学院病理学教研室,陕西西安710069 [2]西北大学西部资源生物与现代生物技术教育部重点实验室,陕西西安710069 [3]西安大兴医院病理科,陕西西安710003 [4]延安大学,陕西延安716000 [5]西北大学信息科学与技术学院,陕西西安710127

出　　处：《现代肿瘤医学》2024年第19期3791-3795,共5页Journal of Modern Oncology

基　　金：国家自然科学基金(编号:82260319,62106198)。

摘　　要：发展人工智能已成为我国的国家战略,其在临床医疗领域的应用日益广泛。在病理学领域,深度学习辅助诊断系统的开发和应用在细胞病理和组织病理检查、免疫组织化学以及分子病理检测等方面都取得了明显进展,许多方面的应用都进入了临床实践。通过深度学习分析病理图像,能够挖掘疾病更深层次的信息,有助于提高病理诊断的客观性和准确性,减少疾病诊断所需的时间和成本,为实现疾病的精确诊疗提供帮助。该文旨在对近些年来深度学习在辅助病理诊断中的应用进展进行综述。The development of artificial intelligence has become China's national strategy,and its application in the field of clinical medicine is increasingly widespread.In the field of pathology,the development and application of deep learning assisted diagnostic systems have made significant progress in cytopathology and histopathological examination,immunohistochemistry and molecular pathology detection,and many applications have entered clinical practice.Through indepth analysis of pathological images,deep learning can mine deeper information of diseases,help to improve the objectivity and accuracy of pathological diagnosis,reduce the time and cost required for disease diagnosis,and provide help for accurate diagnosis and treatment of diseases.This article aims to review the application progress of deep learning in assisting pathological diagnosis in recent years.

关 键 词：病理诊断 人工智能 深度学习 

分 类 号：R730.4[医药卫生—肿瘤]