Large language models in obesity: a systematic review
Authors' conclusion
Generative AI and LLMs show considerable promise for enhancing various aspects of obesity management, from personalized interventions to clinical decision support. However, the current state of the technology exhibits crucial limitations regarding accuracy, consistency, and the ability to handle nuanced clinical situations, mandating a continued critical role for clinician oversight and validation. Further research is imperative to address these shortcomings, focusing on improving model training, validating performance in real-world settings, and addressing ethical considerations before widespread clinical implementation.
Study context
- Population
- Studies investigating the potential role of large language models (LLMs) in obesity medical and surgical care; MEDLINE, OVID and SCOPUS searched from inception to August 202533 studies
- Outcome
- LLM applications in obesity
Methodological detailsnarrative synthesis, ROBINS-I risk of bias assessment
- Narrative synthesis
- ROBINS-I risk of bias assessment
Pooled result
As reported in the abstract
Studies meeting inclusion criteria
33
Original publication
Composed by AI from the published abstract and checked against it. How Briefs are made →