Seeing the random forest through the decision trees. Supporting learning health systems from histopathology with machine learning models: Challenges and opportunities

Q2 Medicine
Ricardo Gonzalez , Ashirbani Saha , Clinton J.V. Campbell , Peyman Nejat , Cynthia Lokker , Andrew P. Norgan
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引用次数: 0

Abstract

This paper discusses some overlooked challenges faced when working with machine learning models for histopathology and presents a novel opportunity to support “Learning Health Systems” with them. Initially, the authors elaborate on these challenges after separating them according to their mitigation strategies: those that need innovative approaches, time, or future technological capabilities and those that require a conceptual reappraisal from a critical perspective. Then, a novel opportunity to support "Learning Health Systems" by integrating hidden information extracted by ML models from digitalized histopathology slides with other healthcare big data is presented.

通过决策树来观察随机森林。用机器学习模型支持组织病理学学习卫生系统:挑战与机遇
本文讨论了在使用组织病理学机器学习模型时面临的一些被忽视的挑战,并提出了一个新的机会来支持“学习健康系统”。最初,作者根据缓解策略将这些挑战区分开来,然后详细阐述了这些挑战:那些需要创新方法、时间或未来技术能力的挑战,以及那些需要从批判性角度重新评估概念的挑战。然后,通过将ML模型从数字化组织病理学幻灯片中提取的隐藏信息与其他医疗保健大数据相结合,提出了一种支持“学习健康系统”的新机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Pathology Informatics
Journal of Pathology Informatics Medicine-Pathology and Forensic Medicine
CiteScore
3.70
自引率
0.00%
发文量
2
审稿时长
18 weeks
期刊介绍: The Journal of Pathology Informatics (JPI) is an open access peer-reviewed journal dedicated to the advancement of pathology informatics. This is the official journal of the Association for Pathology Informatics (API). The journal aims to publish broadly about pathology informatics and freely disseminate all articles worldwide. This journal is of interest to pathologists, informaticians, academics, researchers, health IT specialists, information officers, IT staff, vendors, and anyone with an interest in informatics. We encourage submissions from anyone with an interest in the field of pathology informatics. We publish all types of papers related to pathology informatics including original research articles, technical notes, reviews, viewpoints, commentaries, editorials, symposia, meeting abstracts, book reviews, and correspondence to the editors. All submissions are subject to rigorous peer review by the well-regarded editorial board and by expert referees in appropriate specialties.
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