Work

ChatGPT-4o and 4o1 Preview as Dietary Support Tools in a Real-World Medicated Obesity Program: A Prospective Comparative Analysis

Year: 2025

Type: article

Abstract: BACKGROUND/OBJECTIVES: Clinicians are becoming increasingly interested in the use of large language models (LLMs) in obesity services. While most experts agree that LLM integration would increase access to obesity care and its efficiency, many remain skeptical of their scientific accuracy and capacity to convey human empathy. Recent studies have shown that ChatGPT-3 models are capable of emulating human dietitian responses to a range of basic dietary questions. METHODS: This study compared responses of two ChatGPT-4o models to those from human dietitians across 10 complex questions (5 broad; 5 narrow) derived from patient-clinician interactions within a real-world medicated digital weight loss service. RESULTS: < 0.05) by human dietitians on any of the study's 10 questions. The same finding was made when scores were aggregated from the ten questions across the following four individual study criteria: scientific correctness, comprehensibility, empathy/relatability, and actionability. CONCLUSIONS: These results provide preliminary evidence that advanced LLMs may be able to play a significant supporting role in medicated obesity services. Research in other obesity contexts is needed before any stronger conclusions are made about LLM lifestyle coaching and whether such initiatives increase care access.

Source: Healthcare

DOI: 10.3390/healthcare13060647

Authors: Louis Talay, Leif Lagesen, Adela Yip, Matt Vickers, Neera Ahuja

Institutions: The University of Sydney, Harvard University, Eucalyptus Health (Australia), Stanford Medicine, Stanford University

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,258