Evidence map›Paper›PMID 39782878›Full record

ArticleInternational health2025

Variability of interobserver interpretation of selected helminth ova in the development of a training image set.

Rupert Stephen Charles S Chua, Kiersten A Henderson, Lorenzo Maria C de Guzman, Vicki Foss, Nathaniel Schub, Cameron Bell, John Robert C Medina, Taggart G Siao, Myra S Mistica, Maria Luz B Belleza and 3 more

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Article in International health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Rupert Stephen Charles S ChuaNeglected Tropical Diseases Study Group, National Institutes of Health, University of the Philippines Manila, Manila, Philippines.ORCID 0009-0009-9009-8817
Kiersten A HendersonParasite ID, Corp., Seattle, WA, USA.
Lorenzo Maria C de GuzmanNeglected Tropical Diseases Study Group, National Institutes of Health, University of the Philippines Manila, Manila, Philippines.
Vicki FossParasite ID, Corp., Seattle, WA, USA.
Nathaniel SchubParasite ID, Corp., Seattle, WA, USA.
Cameron BellParasite ID, Corp., Seattle, WA, USA.
John Robert C MedinaInstitute of Clinical Epidemiology, National Institutes of Health, University of the Philippines, Manila, Manila, Philippines.
Taggart G SiaoNeglected Tropical Diseases Study Group, National Institutes of Health, University of the Philippines Manila, Manila, Philippines.
Myra S MisticaDepartment of Parasitology, College of Public Health, University of the Philippines Manila, Manila, Philippines.
Maria Luz B BellezaDepartment of Parasitology, College of Public Health, University of the Philippines Manila, Manila, Philippines.
Marie Cris R ModequilloDepartment of Health Davao Center for Health Development, Davao City, Philippines.
Nadine Joyce C TorresDepartment of Health Caraga Center for Health Development, Butuan City, Philippines.
Vicente Y BelizarioNeglected Tropical Diseases Study Group, National Institutes of Health, University of the Philippines Manila, Manila, Philippines.

Funding

A Machine Learning-Based Mobile Application and Cloud Platform to Enable Accurate and Streamlined Surveillance of Soil-Transmitted Helminth Infection and SchistosomiasisR33TW011753 · FIC · PARASITE ID, CORP. · PI HENDERSON, KIERSTEN · 2022 to 2024
$802k
FIC NIH HHS R33 TW011753NIH HHS R33TW011753
6 · The paper itself

Abstract

backgroundDiagnosis of soil-transmitted helminthiasis and schistosomiasis for surveillance relies on microscopic detection of ova in Kato-Katz (KK) prepared slides. Artificial intelligence (AI)-based platforms for parasitic eggs may be developed using a robust image set with defined labels by reference microscopists. This study aimed to determine interobserver variability among reference microscopists in identifying parasite ova.

methodsImages of parasite ova taken from KK prepared slides were labelled according to species by two reference microscopists (M1 and M2). A third reference microscopist (M3) labelled images when the first two did not agree. Frequency, percent agreement, κ statistics and variability score (VS) were generated for analysis.

resultsM1 and M2 agreed on 89.24% of the labelled images (κ=0.86, p<0.001). M3 had agreement with M1 and M2 (κ=0.30, p<0.001 and κ=0.28, p<0.001), resolving 89.29% of disagreement between them. The labelling of Schistosoma japonicum had the highest VS (κ=0.487, p=0.101) among the targeted ova. Reference microscopists were able to reliably reach consensus in 99.0% of the dataset.

conclusionsTraining AI using this image set may provide more objective and reliable readings compared with that of reference microscopists.

Indexed as

HelminthiasisHelminthsMicroscopyOvumAnimalsArtificial IntelligenceHumansObserver VariationParasite Egg Countartificial intelligenceinterobserver variabilityschistosomiasissoil-transmitted helminths

Identifiers

PMID39782878
PMCPMC12406772

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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.