Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden.
Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland.
JMIR Res Protoc. 2024 Nov 1;13:e58149. doi: 10.2196/58149.
Digital microscopy combined with artificial intelligence (AI) is increasingly being implemented in health care, predominantly in advanced laboratory settings. However, AI-supported digital microscopy could be especially advantageous in primary health care settings, since such methods could improve access to diagnostics via automation and lead to a decreased need for experts on site. To our knowledge, no scoping or systematic review had been published on the use of AI-supported digital microscopy within primary health care laboratories when this scoping review was initiated. A scoping review can guide future research by providing insights to help navigate the challenges of implementing these novel methods in primary health care laboratories.
The objective of this scoping review is to map peer-reviewed studies on AI-supported digital microscopy in primary health care laboratories to generate an overview of the subject.
A systematic search of the databases PubMed, Web of Science, Embase, and IEEE will be conducted. Only peer-reviewed articles in English will be considered, and no limit on publication year will be applied. The concept inclusion criteria in the scoping review include studies that have applied AI-supported digital microscopy with the aim of achieving a diagnosis on the subject level. In addition, the studies must have been performed in the context of primary health care laboratories, as defined by the criteria of not having a pathologist on site and using simple sample preparations. The study selection and data extraction will be performed by 2 independent researchers, and in the case of disagreements, a third researcher will be involved. The results will be presented in a table developed by the researchers, including information on investigated diseases, sample collection, preparation and digitization, AI model used, and results. Furthermore, the results will be described narratively to provide an overview of the studies included. The proposed methodology is in accordance with the JBI methodology for scoping reviews.
The scoping review was initiated in January 2023, and a protocol was published in the Open Science Framework in January 2024. The protocol was completed in March 2024, and the systematic search will be performed after the protocol has been peer reviewed. The scoping review is expected to be finalized by the end of 2024.
A systematic review of studies on AI-supported digital microscopy in primary health care laboratories is anticipated to identify the diseases where these novel methods could be advantageous, along with the shared challenges encountered and approaches taken to address them.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/58149.
数字显微镜结合人工智能（AI）在医疗保健领域的应用日益广泛，主要集中在先进的实验室环境中。然而，人工智能支持的数字显微镜在基层医疗保健环境中可能特别有利，因为这些方法可以通过自动化提高诊断的可及性，并减少现场专家的需求。据我们所知，在本范围综述开始时，尚未发表过关于在基层医疗保健实验室中使用人工智能支持的数字显微镜的综述或系统评价。范围综述可以通过提供见解来指导未来的研究，帮助应对在基层医疗保健实验室中实施这些新方法的挑战。
本范围综述的目的是绘制关于基层医疗保健实验室中人工智能支持的数字显微镜的同行评议研究，以概述该主题。
将对 PubMed、Web of Science、Embase 和 IEEE 数据库进行系统检索。仅考虑英语同行评议文章，且不限制发表年份。范围综述中的概念纳入标准包括旨在实现主题级诊断的应用人工智能支持的数字显微镜的研究。此外，研究必须在基层医疗保健实验室的背景下进行，定义为现场没有病理学家和使用简单样本制备。研究选择和数据提取将由 2 名独立研究人员进行，如果存在分歧，将由第 3 名研究人员参与。结果将以研究人员制定的表格呈现，包括研究中涉及的疾病、样本采集、制备和数字化、使用的 AI 模型以及结果的信息。此外，结果将以叙述的方式描述，以提供对所包括研究的概述。所提出的方法符合 JBI 范围综述方法。
范围综述于 2023 年 1 月启动，并于 2024 年 1 月在开放科学框架中发布了方案。方案于 2024 年 3 月完成，系统检索将在方案经过同行评审后进行。预计范围综述将于 2024 年底完成。
预计对基层医疗保健实验室中人工智能支持的数字显微镜研究的系统评价将确定这些新方法可能有利的疾病，以及遇到的共同挑战和解决这些挑战的方法。
国际注册报告标识符（IRRID）：PRR1-10.2196/58149。
