Evidence map›Paper›PMID 41321681›Full record

Trial reportJournal of nutritional science2025

An automated image-based dietary assessment application: a pilot study.

Lachlan Lee, Rhiane Bishop, James Stanley, He Rourou Whai Painga Consortium

Abstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Journal of nutritional science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Lachlan LeeDepartment of Medicine, University of Otago Wellington, Wellington, New Zealand.ORCID https://orcid.org/0000-0003-4896-9454
Rhiane BishopCentre for Endocrine, Diabetes, and Obesity Research, Wellington, New Zealand.
James StanleyBiostatistics Group, University of Otago Wellington, Wellington, New Zealand.
He Rourou Whai Painga Consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate assessment of an individual's diet is vital to study the effect of diet on health. Image-based methods, which use images as input, may improve the reliability of dietary assessment. We developed an iOS application that uses computer vision to identify food from images. This study aimed to assess the accuracy of energy intake (EI

Indexed as

DietNutrition AssessmentAccelerometryAdultCalorimetry, IndirectDiet RecordsEnergy IntakeEnergy MetabolismFemaleHumansMaleMental RecallMiddle AgedPilot ProjectsReproducibility of ResultsAEE, Activity related energy expenditureDietDietary assessmentDIT, Diet-induced thermogenesisEE, Total energy expenditureEIapp, Energy Intake estimated by the AppEIrecall, Energy Intake estimated by the 24-hour recallsEnergy intakeENMO, Euclidean Norm Minus OneMobile applicationsNutritionREE, Resting energy expenditureVO2, Oxygen consumption

Identifiers

PMID41321681
PMCPMC12658290

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.