Evidence map›Paper›PMID 34467803›Full record

ReviewJournal of diabetes science and technology2023

A Review of Digital Innovations for Diet Monitoring and Precision Nutrition.

Bobak J Mortazavi, Ricardo Gutierrez-Osuna

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of diabetes science and technology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 pooled it
–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

32 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  7. Nutrition as a systems regulator of brain aging trajectories.Frontiers in molecular neuroscience · 2026
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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

2 authors.

Bobak J MortazaviDepartment of Computer Science and Engineering, Texas A&M University, College Station, TX, USA.ORCID 0000-0002-2655-2095
Ricardo Gutierrez-OsunaDepartment of Computer Science and Engineering, Texas A&M University, College Station, TX, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article provides an up-to-date review of technological advances in 3 key areas related to diet monitoring and precision nutrition. First, we review developments in mobile applications, with a focus on food photography and artificial intelligence to facilitate the process of diet monitoring. Second, we review advances in 2 types of wearable and handheld sensors that can potentially be used to fully automate certain aspects of diet logging: physical sensors to detect moments of dietary intake, and chemical sensors to estimate the composition of diets and meals. Finally, we review new programs that can generate personalized/precision nutrition recommendations based on measurements of gut microbiota and continuous glucose monitors with artificial intelligence. The article concludes with a discussion of potential pitfalls of some of these technologies.

Indexed as

Artificial IntelligenceMobile ApplicationsDietEatingHumansNutritional Statusdiet monitoringmachine learningpersonalized nutritionwearable sensors

Identifiers

PMID34467803
PMCPMC9846399

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.