Agreement Between an Artificial Intelligence-Based Meal Image Recognition System and the Weighed Dietary Record for Estimating Energy and Nutrient Intakes.

Akiko Sunto, Kiyoharu Aizawa, Yoko Yamakata, Ayaka Iida, Shihoko Suzuki

Abstract readComparative Study

In one paragraph

Article in Nutrients, 2026. 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

5 authors.

Akiko SuntoSchool of Nutrition and Dietetics, Faculty of Health and Social Services, Kanagawa University of Human Services, Yokohama 238-8522, Japan.ORCID 0000-0001-5956-0262

Kiyoharu AizawaThe University of Tokyo, Tokyo 113-8656, Japan.ORCID 0000-0003-2146-6275

Yoko YamakataInformation Technology Center, The University of Tokyo, Tokyo 113-8656, Japan.ORCID 0000-0003-2752-6179

Ayaka IidaSchool of Nutrition and Dietetics, Faculty of Health and Social Services, Kanagawa University of Human Services, Yokohama 238-8522, Japan.ORCID 0000-0003-2369-1003

Shihoko SuzukiSchool of Nutrition and Dietetics, Faculty of Health and Social Services, Kanagawa University of Human Services, Yokohama 238-8522, Japan.

Funding

Japan Science and Technology Agency (JST) JPMJCR22U4Japan Society for the Promotion of Science (JSPS) JP22K02096; JP23K25247

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Artificial IntelligenceDiet RecordsEnergy IntakeMealsNutrientsAdultFemaleHumansIntelligent SystemsJapanMaleMobile ApplicationsNutrition AssessmentReproducibility of ResultsSmartphoneYoung Adultartificial intelligencedietary surveymeal image recognitionregistered dietitiansmartphone application

Identifiers

PMID41901155

DOI10.3390/nu18060980

PMCPMC13028871

What OpenQuestion holds

Textmetadata

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.