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Document Type

Conference Proceedings

Abstract

Objective: To evaluate recent applications of artificial intelligence (AI) in nutrition counseling and self-management for adults with type 2 diabetes (T2D) and related cardiometabolic conditions. Methods:
A structured literature review identified studies published between 2022–2025 in PubMed and digital health databases examining AI-supported nutrition or lifestyle interventions for adults with T2D. Eligible studies included interventional trials, feasibility or validation studies, and reviews using AI approaches such as machine learning, large language models, retrieval-augmented generation (RAG), digital twins, or image-assisted diet assessment. Extracted variables included study design, AI approach, primary outcomes (glycemic or dietary), usability, and reported limitations. Results: Eight studies met inclusion criteria: RAG-enabled personalized nutrition prototypes improved guideline concordance (80–92%); a digital-twin RCT reduced HbA1c from 9.0 ± 1.9% to 6.1 ± 0.7% (p

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