Artificial Intelligence-Based Diets: A Role in the Nutritional Treatment of Metabolic Dysfunction-Associated Steatotic Liver Disease?

Abstract

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a growing global health concern. Effective management of this condition relies heavily on lifestyle modifications and dietary interventions. In this study, we sought to evaluate the dietary plans for MASLD generated by ChatGPT (GPT-4o) according to current guideline recommendations. Methods: ChatGPT was used to create single-day meal plans for 48 simulated patients with MASLD, tailored to individual characteristics such as age, gender, height, weight and transient elastography parameters. The plans were assessed for appropriateness according to disease-specific guidelines. Results: The mean energy content of the menus planned by ChatGPT was 1596.9 +/- 141.5 kcal with a mean accuracy of 91.3 +/- 11.0%, and fibre content was 22.0 +/- 0.6 g with a mean accuracy of 88.1 +/- 2.5%. However, they exhibited elevated levels of protein, fat and saturated fat acids. Conversely, the carbohydrate content was lower. ChatGPT recommended weight loss for obese patients but did not extend this advice to normal-weight and overweight individuals. Notably, recommendations for a Mediterranean diet and physical activity were absent. Conclusions: ChatGPT shows potential in developing dietary plans for MASLD management. However, discrepancies in macronutrient distributions and the omission of key evidence-based recommendations highlight the need for further refinement. To enhance the effectiveness of AI tools in dietary recommendations, alignment with established guidelines must be improved.