ArticleZhonghua xue ye xue za zhi = Zhonghua xueyexue zazhi2024
[Chinese expert consensus on the technical and clinical practice specifications of artificial intelligence assisted morphology examination of blood cells (2024)].
Article in Zhonghua xue ye xue za zhi = Zhonghua xueyexue zazhi, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Deep Learning Identifies Abnormal Promyelocytes in Peripheral Blood Based on Morphological Analysis.Diagnostics (Basel, Switzerland) · 2026Article
- A large dataset of bone marrow cells in myelodysplastic syndrome for classification systems.Scientific data · 2025Article
- [Advancements in artificial intelligence for the precise diagnosis and treatment of hematological malignancies].Zhonghua xue ye xue za zhi = Zhonghua xueyexue zazhi · 2025Review
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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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