Digital pathology and artificial intelligence as the next chapter in diagnostic hematopathology
Digital pathology and artificial intelligence as the next chapter in diagnostic hematopathology
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DOI：
10.1053/j.semdp.2023.02.001
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发表时间：
2023-03-11
影响因子：
2.3
通讯作者：
Chen, Mingyi
中科院分区：
文献类型：
--
作者：
Lin, Elisa;Fuda, Franklin;Chen, Mingyi
数字病理学在诊断病理学中起着至关重要的作用，并且越来越成为该领域的技术要求。将数字载玻片集成到病理学工作流程中，先进的算法和计算机辅助诊断技术将病理学家的视野扩展到显微镜载玻片之外，并实现知识和专业知识的真正整合。人工智能（AI）在病理学和血液病理学领域有着明显的突破潜力，本文将讨论机器学习在血液淋巴疾病的诊断、分类和治疗指南中的应用方法，以及人工智能在血液淋巴疾病流式细胞术分析中的最新进展。我们审查这些主题，特别是通过潜在的临床应用CellaVision，外周血的自动数字图像分析仪，Morphogo，一种新的人工智能为基础的骨髓分析系统。采用这些新技术将使病理学家能够简化工作流程，并在诊断血液病方面实现更快的周转时间。
Digital pathology has a crucial role in diagnostic pathology and is increasingly a technological requirement in the field. Integration of digital slides into the pathology workflow, advanced algorithms, and computer-aided diagnostic techniques extend the frontiers of the pathologist's view beyond the microscopic slide and enable true integration of knowledge and expertise. There is clear potential for artificial intelligence (AI) breakthroughs in pathology and hematopathology.In this review article, we discuss the approach of using machine learning in the diagnosis, classification, and treatment guidelines of hematolymphoid disease, as well as recent progress of artificial intelligence in flow cytometric analysis of hematolymphoid diseases. We review these topics specifically through the potential clinical applications of CellaVision, an automated digital image analyzer of peripheral blood, and Morphogo, a novel artificial intelligence-based bone marrow analyzing system. Adoption of these new technologies will allow pathologists to streamline workflow and achieve faster turnaround time in diagnosing hematological disease.