ArticlePublic health nutrition2021
The potential of artificial intelligence in enhancing adult weight loss: a scoping review.
Article in Public health nutrition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.
What it found
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The trial behind it
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Who cites it
24 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Pooled it
- Sustainability of Weight Loss Through Smartphone Apps: Systematic Review and Meta-analysis on Anthropometric, Metabolic, and Dietary Outcomes.Journal of medical Internet research · 2022Pooled it
- Artificial Intelligence Interventions Targeting Obesity-Related Behaviors: Protocol for a Scoping Review.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026Article
- Artificial intelligence in public health-challenges and opportunities.European journal of clinical nutrition · 2026Review
- Adherence to Behavioral Weight Management: A Scoping Review of Definitions, Measurement, and Components.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026Article
- Artificial intelligence applications for assessing ultra-processed food consumption: a scoping review.The British journal of nutrition · 2026Article
- Artificial intelligence in obesity management: clinical evidence, translational gaps, and implementation priorities-a structured narrative review.Frontiers in endocrinology · 2026Review
- The Use of Artificial Intelligence (AI) to Support Dietetic Practice Across Primary Care: A Scoping Review of the Literature.Nutrients · 2025Article
- Multimodal and Multidimensional Artificial Intelligence Technology in Obesity.Journal of obesity & metabolic syndrome · 2025Review
- Artificial Intelligence in Health Promotion and Disease Reduction: Rapid Review.Journal of medical Internet research · 2025Review
- Opportunities for General Internal Medicine to Promote Equity in Obesity Care.Journal of general internal medicine · 2025Article
- Assessing online chat-based artificial intelligence models for weight loss recommendation appropriateness and bias in the presence of guideline incongruence.International journal of obesity (2005) · 2025Article
- Impact of machine learning on dietary and exercise behaviors in type 2 diabetes self-management: a systematic literature review.PeerJ. Computer science · 2025Article
- A systematic review of obesity burden in Saudi Arabia: Prevalence and associated co-morbidities.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2024Review
- Effectiveness of an Artificial Intelligence-Assisted App for Improving Eating Behaviors: Mixed Methods Evaluation.Journal of medical Internet research · 2024Article
- [Dietary Management of Obesity].The Korean journal of gastroenterology = Taehan Sohwagi Hakhoe chi · 2024Review
- Strategies to Improve Physical Activity and Nutrition Behaviours in Children and Adolescents: A Review.Nutrients · 2023Review
- Artificial intelligence and obesity management: An Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) 2023.Obesity pillars · 2023Article
- Personal motivation, self-regulation barriers and strategies for weight loss in people with overweight and obesity: a thematic framework analysis.Public health nutrition · 2022Article
- What Intervention Elements Drive Weight Loss in Blended-Care Behavior Change Interventions? A Real-World Data Analysis with 25,706 Patients.Nutrients · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo present an overview of how artificial intelligence (AI) could be used to regulate eating and dietary behaviours, exercise behaviours and weight loss.
designA scoping review of global literature published from inception to 15 December 2020 was conducted according to Arksey and O'Malley's five-step framework. Eight databases (CINAHL, Cochrane-Central, Embase, IEEE Xplore, PsycINFO, PubMed, Scopus and Web of Science) were searched. Included studies were independently screened for eligibility by two reviewers with good interrater reliability (k = 0·96).
resultsSixty-six out of 5573 potential studies were included, representing more than 2031 participants. Three tenets of self-regulation were identified - self-monitoring (n 66, 100 %), optimisation of goal setting (n 10, 15·2 %) and self-control (n 10, 15·2 %). Articles were also categorised into three AI applications, namely machine perception (n 50), predictive analytics only (n 6) and real-time analytics with personalised micro-interventions (n 10). Machine perception focused on recognising food items, eating behaviours, physical activities and estimating energy balance. Predictive analytics focused on predicting weight loss, intervention adherence, dietary lapses and emotional eating. Studies on the last theme focused on evaluating AI-assisted weight management interventions that instantaneously collected behavioural data, optimised prediction models for behavioural lapse events and enhance behavioural self-control through adaptive and personalised nudges/prompts. Only six studies reported average weight losses (2·4-4·7 %) of which two were statistically significant.
conclusionThe use of AI for weight loss is still undeveloped. Based on the current study findings, we proposed a framework on the applicability of AI for weight loss but cautioned its contingency upon engagement and contextualisation.
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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.