闭环--病理学家在数字和计算病理学研究中的作用。

IF 3.4 2区 医学 Q1 PATHOLOGY
Tilman T Rau, William Cross, Ricardo R Lastra, Regina C-L Lo, Andres Matoso, C Simon Herrington
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引用次数: 0

摘要

病理学杂志》正在收到越来越多与数字和计算病理学相关的稿件:临床研究》投稿数量不断增加,这是数字成像和基于算法的数字病理学向计算病理学和人工智能不断发展的一部分。然而,尽管取得了这些技术进步,组织分析仍然在很大程度上依赖于病理学家的注释。病理学家在标注任务中的角色有三个关键要素:精细度、时间限制和对计算结果的解释责任。粒度涉及详细注释,包括病例级别、区域和细胞特征;以及整合不同来源的归因。病理学家短缺造成的时间限制促使人们开发出各种技术,以加快从细胞级归因到所谓无监督学习的注释任务。病理学家的影响力似乎有所减弱,但他们在提供基本事实以及将病理知识生成与计算进步联系起来方面发挥着至关重要的作用。为了在人机交互过程中保持真实性,必须采取措施将结果显示给病理学家,并对正确应用的诊断标准进行反思。协作和迭代过程,如人在回路中的机器学习,是持续改进的关键,可确保病理学家参与评估计算结果,实现临床应用的闭环。本刊尤其关注计算病理学在临床诊断中的应用,欢迎针对本社论提出的问题投稿。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Closing the loop – the role of pathologists in digital and computational pathology research

An increasing number of manuscripts related to digital and computational pathology are being submitted to The Journal of Pathology: Clinical Research as part of the continuous evolution from digital imaging and algorithm-based digital pathology to computational pathology and artificial intelligence. However, despite these technological advances, tissue analysis still relies heavily on pathologists' annotations. There are three crucial elements to the pathologist's role during annotation tasks: granularity, time constraints, and responsibility for the interpretation of computational results. Granularity involves detailed annotations, including case level, regional, and cellular features; and integration of attributions from different sources. Time constraints due to pathologist shortages have led to the development of techniques to expedite annotation tasks from cell-level attributions up to so-called unsupervised learning. The impact of pathologists may seem diminished, but their role is crucial in providing ground truth and connecting pathological knowledge generation with computational advancements. Measures to display results back to pathologists and reflections about correctly applied diagnostic criteria are mandatory to maintain fidelity during human–machine interactions. Collaboration and iterative processes, such as human-in-the-loop machine learning are key for continuous improvement, ensuring the pathologist's involvement in evaluating computational results and closing the loop for clinical applicability. The journal is interested particularly in the clinical diagnostic application of computational pathology and invites submissions that address the issues raised in this editorial.

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来源期刊
Journal of Pathology Clinical Research
Journal of Pathology Clinical Research Medicine-Pathology and Forensic Medicine
CiteScore
7.40
自引率
2.40%
发文量
47
审稿时长
20 weeks
期刊介绍: The Journal of Pathology: Clinical Research and The Journal of Pathology serve as translational bridges between basic biomedical science and clinical medicine with particular emphasis on, but not restricted to, tissue based studies. The focus of The Journal of Pathology: Clinical Research is the publication of studies that illuminate the clinical relevance of research in the broad area of the study of disease. Appropriately powered and validated studies with novel diagnostic, prognostic and predictive significance, and biomarker discover and validation, will be welcomed. Studies with a predominantly mechanistic basis will be more appropriate for the companion Journal of Pathology.
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