Using mobile applications for body composition analysis: A technical review of an artificial intelligence-based tool

MeThreeSixty app used 3D imaging and AI with acceptable group-level accuracy for estimating body circumference and composition, but limited precision at the individual level requires cautious interpretation. Further prospective validation and model refinement are needed, especially in diverse populations, and using longitudinal datasets before supporting personalized nutrition and broader health platform integration.

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Publication Details

Journal
Clinical Nutrition ESPEN
Published
2026-03-09
DOI
https://doi.org/10.1016/j.clnesp.2026.103105
Primary Topic
Body Composition Measurement Techniques
Type
article
Field-Weighted Citation Impact
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article

Using mobile applications for body composition analysis: A technical review of an artificial intelligence-based tool

Taiara Scopel Poltronieri, Steven B. Heymsfield, Bruna R. da Silva, Carla M. Prado et al.
Clinical Nutrition ESPEN
Body Composition Measurement Techniques
article

Using mobile applications for body composition analysis: A technical review of an artificial intelligence-based tool

Taiara Scopel Poltronieri, Steven B. Heymsfield, Bruna R. da Silva, Carla M. Prado, John A. Shepherd, Jonathan Bennett
article en

Abstract

MeThreeSixty app used 3D imaging and AI with acceptable group-level accuracy for estimating body circumference and composition, but limited precision at the individual level requires cautious interpretation. Further prospective validation and model refinement are needed, especially in diverse populations, and using longitudinal datasets before supporting personalized nutrition and broader health platform integration.

Clinical Nutrition ESPENVol. 73
Pennington Biomedical Research Center (US), Universidade Federal do Rio Grande do Sul (BR), University of Alberta (CA), Cancer Center of Hawaii (US)
Openalex Percentile: Top 27%
Body Composition Measurement Techniques
DOIOpen Access PDFOpenAlex
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