Summary
This scoping review surveys the emerging landscape of artificial intelligence-assisted dietary assessment tools and their potential applications in clinical nutrition practice. The authors examine how machine learning and algorithmic approaches might enhance traditional dietary assessment methods, whilst identifying evidence gaps and implementation challenges. The review contributes to understanding how digital innovations could support more efficient and personalised nutrition care delivery, though practical adoption barriers in healthcare settings remain significant.
UK applicability
Findings are relevant to UK dietetic practice and NHS nutrition services, particularly as digital health integration advances. However, implementation would require alignment with UK regulatory frameworks, data governance standards, and integration with existing electronic health record systems.
Key measures
Types of AI-assisted dietary assessment tools identified; applications in nutrition care; evidence quality and gaps; feasibility and implementation considerations
Outcomes reported
A scoping review examining the potential applications, capabilities and limitations of AI-assisted tools for dietary assessment in clinical nutrition practice. The study synthesises evidence on how next-generation digital nutrition assessment technologies may support personalised nutrition care delivery.
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