Evidence map›Paper›PMID 39486020›Full record

ArticleJMIR research protocols2024

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

Joar von Bahr, Vinod Diwan, Andreas Mårtensson, Nina Linder, Johan Lundin

Abstract read
In one paragraph

Article in JMIR research protocols, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Joar von BahrDepartment of Global Public Health, Karolinska Institutet, Stockholm, Sweden.ORCID 0009-0009-8687-2160
Vinod DiwanDepartment of Global Public Health, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0002-5831-2037
Andreas MårtenssonGlobal Health and Migration Unit, Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden.ORCID 0000-0001-7504-8365
Nina Linder *Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland.ORCID 0000-0003-3930-0513
Johan Lundin *Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0002-2681-4139

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital 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.

objectiveThe 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.

methodsA 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.

resultsThe 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.

conclusionsA 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.

Indexed as

Artificial IntelligenceMicroscopyPrimary Health CareHumansScoping Reviews as TopicAIartificial intelligenceconvolutional neural networkdeep learningdiagnosisdigital diagnosticsmachine learningpathologyprimary health carewhole slide images

Identifiers

PMID39486020
PMCPMC11568397

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.