AI-Supported Digital Microscopy Diagnostics in Primary Health Care Laboratories: Protocol for a Scoping Review.

IF 1.4 Q3 HEALTH CARE SCIENCES & SERVICES JMIR Research Protocols Pub Date : 2024-11-01 DOI:10.2196/58149
Joar von Bahr, Vinod Diwan, Andreas Mårtensson, Nina Linder, Johan Lundin
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Abstract

Background: 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.

Objective: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

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初级卫生保健实验室的人工智能支持数字显微镜诊断:范围审查协议》。
背景:结合人工智能(AI)的数码显微技术正越来越多地应用于医疗保健领域,主要是在高级实验室环境中。然而,人工智能支持的数字显微镜技术在初级医疗机构中尤其具有优势,因为这种方法可以通过自动化提高诊断的可及性,从而减少对现场专家的需求。据我们所知,在启动本范围界定综述时,还没有关于在初级卫生保健实验室中使用人工智能支持的数码显微镜的范围界定或系统综述。范围界定综述可以为未来的研究提供指导,提供见解,帮助应对在初级卫生保健实验室实施这些新方法所面临的挑战:本范围界定综述的目的是对初级卫生保健实验室中人工智能支持的数字显微镜的同行评审研究进行摸底,以便对该主题进行概述:方法:将对 PubMed、Web of Science、Embase 和 IEEE 等数据库进行系统检索。只考虑同行评审过的英文文章,不限制发表年份。范围界定审查的概念纳入标准包括应用人工智能支持的数字显微镜进行研究,目的是实现学科层面的诊断。此外,这些研究必须是在初级卫生保健实验室中进行的,其标准是现场没有病理学家并使用简单的样本制备方法。研究选择和数据提取将由两名独立研究人员进行,如果出现分歧,将由第三名研究人员参与。研究结果将以研究人员制定的表格形式呈现,包括所调查疾病的信息、样本采集、制备和数字化、所使用的人工智能模型以及结果。此外,还将对结果进行叙述性说明,以提供所纳入研究的概况。建议采用的方法与 JBI 的范围界定审查方法一致:范围界定审查于 2023 年 1 月启动,并于 2024 年 1 月在开放科学框架中发布了审查协议。协议于 2024 年 3 月完成,系统检索将在协议通过同行评审后进行。范围界定审查预计将于 2024 年底完成:对初级卫生保健实验室中人工智能支持的数字显微镜的研究进行系统综述,预计将确定这些新方法可能具有优势的疾病,以及遇到的共同挑战和解决这些挑战的方法:PRR1-10.2196/58149。
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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5.90%
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414
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