ArticleHealth psychology research2020
A review on food recognition technology for health applications.
Article in Health psychology research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 51 citations in OpenAlex.
- Technology to Automatically Record Eating Behavior in Real Life: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- Nutrigenomics meets multi-omics: integrating genetic, metabolic, and microbiome data for personalized nutrition strategies.Genes & nutrition · 2025Review
- Food Image Recognition Based on Anti-Noise Learning and Covariance Feature Enhancement.Foods (Basel, Switzerland) · 2025Article
- Artificial Intelligence Applications to Measure Food and Nutrient Intakes: Scoping Review.Journal of medical Internet research · 2024Article
- Article
- Image-Based Volume Estimation for Food in a Bowl.Journal of food engineering · 2024Article
- Decoding Heterogeneity in Data-Driven Self-Monitoring Adherence Trajectories in Digital Lifestyle Interventions for Weight Loss: A Qualitative Study.Research square · 2024Article
- A Lightweight Hybrid Model with Location-Preserving ViT for Efficient Food Recognition.Nutrients · 2024Article
- Long-Tailed Food Classification.Nutrients · 2023Article
- Article
- Development and User Evaluation of a Food-recognition app (FoodRec): Experimental Data and Qualitative Analysis.Health psychology research · 2023Article
- A Novel Approach to Dining Bowl Reconstruction for Image-Based Food Volume Estimation.Sensors (Basel, Switzerland) · 2022Article
- A Novel Digital Nutrition Diary for Geriatric Patients at High Risk of Frailty Syndrome.Nutrients · 2022Article
- Innovative new model predicts glucose levels without poking or prodding.NPJ digital medicine · 2021Article
- MyDietCam: Development and usability study of a food recognition integrated dietary monitoring smartphone application.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Food understanding from digital media has become a challenge with important applications in many different domains. On the other hand, food is a crucial part of human life since the health is strictly affected by diet. The impact of food in people life led Computer Vision specialists to develop new methods for automatic food intake monitoring and food logging. In this review paper we provide an overview about automatic food intake monitoring, by focusing on technical aspects and Computer Vision works which solve the main involved tasks (
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.