ArticleFrontiers in psychiatry2024
An advanced Artificial Intelligence platform for a personalised treatment of Eating Disorders.
Article in Frontiers in psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
What it found
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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.
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Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Neuroimaging and machine learning in eating disorders: a systematic review.Eating and weight disorders : EWD · 2025Pooled it
- Effectiveness of written emotional disclosure interventions for eating disorders: a systematic review and meta-analysis.Frontiers in nutrition · 2024Pooled it
- How do Artificial Intelligence chatbots respond to questions from adolescent personas about their eating, body weight or appearance?Child and adolescent mental health · 2026Article
- Artificial Intelligence in Clinical Nutrition: Current Uses, Challenges, and Opportunities.Nutrients · 2026Review
- Leveraging artificial intelligence to personalize treatment for eating disorders: A proof-of-concept study.Journal of affective disorders · 2026Article
- Conditional Acceptance and the Optimism-Knowledge Gap: A Scoping Review of Attitudes and Perceptions of Artificial Intelligence in Healthcare in Italy.Medical sciences (Basel, Switzerland) · 2026Article
- P5 Mental Health Platform: A Digital Solution to Monitor Anxiety and Depression Symptoms in the General Portuguese Population.Epidemiologia (Basel, Switzerland) · 2026Article
- Article
- Perspectives of Non-Medical Professionals Working in a Mental Health Service on Eating Disorders: Awareness, Knowledge, and Stigmatisation.Nutrients · 2025Article
- Examining the biological causes of eating disorders to inform treatment strategies.Nature reviews. Neuroscience · 2025Review
- Effect of ChatGPT use on eating disorders and body image.World journal of psychiatry · 2025Review
- Ethical decision-making for AI in mental health: the Integrated Ethical Approach for Computational Psychiatry (IEACP) framework.Psychological medicine · 2025Review
- Treating the individual: moving towards personalised eating disorder care.Journal of eating disorders · 2025Review
- The Role of Artificial Intelligence in Managing Bipolar Disorder: A New Frontier in Patient Care.Journal of clinical medicine · 2025Article
- Precision Psychiatry for Obsessive-Compulsive Disorder: Clinical Applications of Deep Learning Architectures.Journal of clinical medicine · 2025Review
- A validity and reliability study of the artificial intelligence attitude scale (AIAS-4) and its relationship with social media addiction and eating behaviors in Turkish adults.BMC public health · 2025Article
- Journey Mapping for Symptom Management in Adolescents with Depression: A Longitudinal Qualitative Study of Dynamic Patient-Centered Pathways.Journal of multidisciplinary healthcare · 2025Article
- Proximity-based solutions for optimizing autism spectrum disorder treatment: integrating clinical and process data for personalized care.Frontiers in psychiatry · 2024Article
- Artificial intelligence in psychiatry: A systematic review and meta-analysis of diagnostic and therapeutic efficacy.Digital healthReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Eating Disorders (EDs) affect individuals globally and are associated with significant physical and mental health challenges. However, access to adequate treatment is often hindered by societal stigma, limited awareness, and resource constraints. Methods: The project aims to utilize the power of Artificial Intelligence (AI), particularly Machine Learning (ML) and Deep Learning (DL), to improve EDs diagnosis and treatment. The Master Data Plan (MDP) will collect and analyze data from diverse sources, utilize AI algorithms for risk factor identificat io n, treatment planning, and relapse prediction, and provide a patient-facing chatbot for information and support. This platform will integrate patient data, support healthcare professionals, and empower patients, thereby enhancing care accessibility, personalizing treatment plans, and optimizing care pathways. Robust data governance measures will ensure ethical and secure data management. Results: Anticipated outcomes include enhanced care accessibility and efficiency, personalized treatment plans leading to improved patient outcomes, reduced waiting lists, heightened patient engagement, and increased awareness of EDs with improved resource allocation. Discussion: This project signifies a pivotal shift towards data-driven, patient-centered ED care in Italy. By integrat ing AI and promoting collaboration, it seeks to redefine mental healthcare standards and foster better well- being among individuals with EDs.
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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.