ArticleNPJ digital medicine2025
Advances in the estimation of body fat percentage using an artificial intelligence 2D-photo method.
Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
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Who cites it
3 citing papers in PubMed.
- AI-Based Measurement Tools for Intrinsic Capacity in Older Adults: Scoping Review.Journal of medical Internet research · 2026Article
- EfficientPoseSegNet: a weakly supervised, attention-guided framework for human pose estimation, anatomical segmentation, and concealed object detection in backscatter millimeter-wave security screening.Scientific reports · 2025Article
- Use of Handgrip Strength as a Health Indicator in Public Sector Workers: A Cross-Sectional Study.Journal of functional morphology and kinesiology · 2025Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There is a growing need to evaluate the agreement between the field methods and integrate artificial intelligence (AI) using two-dimensional (2D) photos for enhanced real-world analysis. This study evaluated the agreement between AI-2D photos and the clinical reference method, dual-energy X-ray absorptiometry (DXA) to estimate the body fat percentage (BFP). Other methods were also investigated, including skinfolds, A-mode ultrasound, and bioelectrical impedance analysis (BIA). This cross-sectional study was conducted on 1273 adults of both sexes. The Bland-Altman plots, Lin's Correlation Coefficient of Agreement (CCC), and error analyses were calculated. AI-2D photos demonstrated substantial agreement with DXA presenting the highest agreement (CCC ≥ 0.96) among all the investigated methods. InBody-270 and Omron HBF-514 BIA devices showed moderate agreement (CCC = 0.90 to 0.95) for all participants, age groups >30 years, and body mass index >25 kg/m
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Registered trials
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