Potential Use of ChatGPT-4 in Micronutrient Deficiency Management: A Narrative Scoping Review and a Framework for Validation and Safe Deployment

Abstract / Summary

Micronutrient deficiencies remain common and clinically important, yet their recognition and management require careful history-taking, appropriate testing, and guideline-concordant counseling. Large language models (LLMs) such as ChatGPT-4 have been proposed as tools that may support clinical nutrition workflows; however, their capabilities and limitations are frequently misunderstood, and their safe use requires rigorous validation. This article provides a narrative scoping synthesis of plausible use cases for ChatGPT-4 across micronutrient deficiency care (e.g., structured symptom–diet–medication history elicitation, drafting clinician-facing summaries, and preparing patient education materials) while explicitly noting that ChatGPT-4 is not an autonomous diagnostic system, does not access real-time biomedical databases, and cannot replace clinician judgment. The authors then propose a practical framework for validation and safe deployment, including task definitions, standardized prompt templates, comparison baselines (clinician-authored outputs and rule-based checklists, and where appropriate predictive machine learning [ML] models), clinician annotation with quality assurance, and an error taxonomy emphasizing hallucinations, guideline discordance, inappropriate certainty, and missed red flags. Finally, the authors discuss governance considerations relevant to clinical journals, including training-data cutoff and guideline drift, accountability, regulation, and medico-legal risk. Overall, ChatGPT-4 may be useful as a supportive language interface within clinician-supervised systems, but clinical adoption should be contingent on transparent benchmarking, safety evaluation, and clear responsibility frameworks.

Cite this article as: Aydin A, Arslan S. Potential use of ChatGPT-4 in micronutrient deficiency management: a narrative scoping review and a framework for validation and safe deployment. Cerrahpaşa Med J. 2026, 50, 0115, doi: 10.5152/cjm.2026.25115.