ArticleEuropean eating disorders review : the journal of the Eating Disorders Association2021
Machine learning to advance the prediction, prevention and treatment of eating disorders.
Article in European eating disorders review : the journal of the Eating Disorders Association, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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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.
The trial behind it
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Who cites it
14 citing papers in PubMed, 25 citations in OpenAlex.
- Negative and Positive Body-Related Emotions Derived From Voice Recordings During a Mirror Task in Anorexia and Bulimia Nervosa: A Natural Language Processing Approach Using RoBERTa.The International journal of eating disorders · 2026Article
- "Developing machine learning models of self-reported and register-based data to predict eating disorders in adolescence".Npj mental health research · 2025Article
- Predicting anorexia nervosa treatment efficacy: an explainable machine learning approach.Journal of eating disorders · 2025Article
- Predictive assessment of eating disorder risk and recovery: Uncovering the effectiveness of questionnaires and influencing characteristics.Computational and structural biotechnology journal · 2025Article
- Differentiation between atypical anorexia nervosa and anorexia nervosa using machine learning.The International journal of eating disorders · 2024Article
- Using machine learning with passive wearable sensors to pilot the detection of eating disorder behaviors in everyday life.Psychological medicine · 2024Article
- An advanced Artificial Intelligence platform for a personalised treatment of Eating Disorders.Frontiers in psychiatry · 2024Article
- Development of transdiagnostic clinical risk prediction models for 12-month onset and course of eating disorders among adolescents in the community.The International journal of eating disorders · 2023Article
- Predictors of Treatment Outcome in Eating Disorders: A Roadmap to Inform Future Research Efforts.Current psychiatry reports · 2023Review
- Machine learning research based on diffusion tensor images to distinguish between anorexia nervosa and bulimia nervosa.Frontiers in psychiatry · 2023Article
- Acute coronary syndrome screening in patients presenting with arteriosclerosis in health check-ups: a case-control study.BMJ open · 2022Article
- Potential benefits and limitations of machine learning in the field of eating disorders: current research and future directions.Journal of eating disorders · 2022Review
- Traditional Machine Learning Models and Bidirectional Encoder Representations From Transformer (BERT)-Based Automatic Classification of Tweets About Eating Disorders: Algorithm Development and Validation Study.JMIR medical informatics · 2022Article
- Machine learning approach identified clusters for patients with low cardiac output syndrome and outcomes after cardiac surgery.Frontiers in cardiovascular medicine · 2022Article
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
Machine learning approaches are just emerging in eating disorders research. Promising early results suggest that such approaches may be a particularly promising and fruitful future direction. However, there are several challenges related to the nature of eating disorders in building robust, reliable and clinically meaningful prediction models. This article aims to provide a brief introduction to machine learning and to discuss several such challenges, including issues of sample size, measurement, imbalanced data and bias; I also provide concrete steps and recommendations for each of these issues. Finally, I outline key outstanding questions and directions for future research in building, testing and implementing machine learning models to advance our prediction, prevention, and treatment of eating disorders.
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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.