Artificial intelligence as a tool for diagnosis in digital pathology whole slide images: A systematic review

数字化病理学 计算机科学 经济短缺 数据科学 领域(数学) 数字图像分析 心灵感应学 人工智能应用 质量(理念) 人工智能 病理 医学物理学 医学 计算机视觉 医疗保健 远程医疗 哲学 认识论 经济 经济增长 纯数学 语言学 数学 政府(语言学)
作者
João Pedro Mazuco Rodriguez,Rubens Rodriguez,Vitor Werneck Krauss Silva,Felipe Kitamura,Gustavo Cesar Antônio Corradi,Ana Carolina Bertoletti De Marchi,Rafael Rieder
出处
期刊:Journal of pathology informatics [Medknow Publications]
卷期号:13: 100138-100138 被引量:11
标识
DOI:10.1016/j.jpi.2022.100138
摘要

Digital pathology had a recent growth, stimulated by the implementation of digital whole slide images (WSIs) in clinical practice, and the pathology field faces shortage of pathologists in the last few years. This scenario created fronts of research applying artificial intelligence (AI) to help pathologists. One of them is the automated diagnosis, helping in the clinical decision support, increasing efficiency and quality of diagnosis. However, the complexity nature of the WSIs requires special treatments to create a reliable AI model for diagnosis. Therefore, we systematically reviewed the literature to analyze and discuss all the methods and results in AI in digital pathology performed in WSIs on H&E stain, investigating the capacity of AI as a diagnostic support tool for the pathologist in the routine real-world scenario. This review analyzes 26 studies, reporting in detail all the best methods to apply AI as a diagnostic tool, as well as the main limitations, and suggests new ideas to improve the AI field in digital pathology as a whole. We hope that this study could lead to a better use of AI as a diagnostic tool in pathology, helping future researchers in the development of new studies and projects.

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