Abstract：
Blood cell morphological examination is a crucial method for the diagnosis of blood diseases, but traditional manual microscopy is characterized by low efficiency and susceptibility to subjective biases. The application of artificial intelligence (AI) technology has improved the efficiency and quality of blood cell examinations and facilitated the standardization of test results. Currently, a variety of AI devices are either in clinical use or under research, with diverse technical requirements and configurations. The Experimental Diagnostic Study Group of the Hematology Branch of the Chinese Medical Association has organized a panel of experts to formulate this consensus. The consensus covers term definitions, scope of application, technical requirements, clinical application, data management, and information security. It emphasizes the importance of specimen preparation, image acquisition, image segmentation algorithms, and cell feature extraction and classification, and sets forth basic requirements for the cell recognition spectrum. Moreover, it provides detailed explanations regarding the fine classification of pathological cells, requirements for cell training and testing, quality control standards, and assistance in issuing diagnostic reports by humans. Additionally, the consensus underscores the significance of data management and information security to ensure the safety of patient information and the accuracy of data.
血细胞形态学检查是血液疾病诊断的重要手段，传统人工镜检存在效率低、易受主观影响等问题。人工智能技术的应用提高了血细胞检查的效率和质量，促进了检测结果的标准化。目前，多种人工智能设备已在临床使用或研究中，但其技术要求和配置各异。中华医学会血液学分会实验诊断学组组织相关专家，制订了本共识。本共识内容包括术语定义、适用范围、技术要求、临床应用、数据管理和信息安全，强调了标本制备、图像采集、图像分割算法、细胞特征提取与识别分类的重要性，并提出了细胞识别谱的基本要求。同时，对病理细胞的细分类、细胞训练与测试的要求、质量控制标准、辅助人工出具诊断报告等方面进行了详细说明。此外，还强调了数据管理和信息安全的重要性，确保患者信息的安全和数据的准确性。.
血细胞形态学检查是血液疾病诊断的重要手段，传统人工镜检存在效率低、易受主观影响等问题。人工智能技术的应用提高了血细胞检查的效率和质量，促进了检测结果的标准化。目前，多种人工智能设备已在临床使用或研究中，但其技术要求和配置各异。中华医学会血液学分会实验诊断学组组织相关专家，制订了本共识。本共识内容包括术语定义、适用范围、技术要求、临床应用、数据管理和信息安全，强调了标本制备、图像采集、图像分割算法、细胞特征提取与识别分类的重要性，并提出了细胞识别谱的基本要求。同时，对病理细胞的细分类、细胞训练与测试的要求、质量控制标准、辅助人工出具诊断报告等方面进行了详细说明。此外，还强调了数据管理和信息安全的重要性，确保患者信息的安全和数据的准确性。.
摘要：
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