[Chinese expert consensus on the technical and clinical practice specifications of artificial intelligence assisted morphology examination of blood cells (2024)].

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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.

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[人工智能辅助血细胞形态学检查技术和临床实践规范(2024 年)中国专家共识]。
血细胞形态学检查是诊断血液疾病的重要方法,但传统的人工显微镜检查存在效率低、易受主观偏见影响等问题。人工智能(AI)技术的应用提高了血细胞检查的效率和质量,促进了检查结果的标准化。目前,各种人工智能设备或已投入临床使用,或正在研究之中,其技术要求和配置各不相同。中华医学会血液学分会实验诊断学组组织专家组制定了本共识。该共识涵盖术语定义、应用范围、技术要求、临床应用、数据管理和信息安全等方面。它强调了标本制备、图像采集、图像分割算法、细胞特征提取与分类的重要性,并提出了细胞识别图谱的基本要求。此外,它还详细解释了病理细胞的精细分类、细胞培训和测试要求、质量控制标准,以及协助人类出具诊断报告。此外,共识还强调了数据管理和信息安全的重要性,以确保患者信息的安全性和数据的准确性。
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CiteScore
0.80
自引率
0.00%
发文量
100
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