GlyTwin generates patient-centric counterfactual behavioral interventions to reduce hyperglycemia in type 1 diabetes, evaluated on a new dataset from 50 patients showing 85.8% valid explanations and 87.3% effectiveness.
Designing user-centric behavioral interventions to prevent dysg- lycemia with novel counterfactual explanations
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MetaPlate combines a glucose-response ML model, counterfactual meal optimization, and RAG-LLM to generate personalized recommendations that keep post-meal glucose ≤140 mg/dL, with dietitian ratings improving after prompt changes.
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MetaPlate: Counterfactual-Guided RAG-LLM Tool for Personalized Food Recommendation and Hyperglycemia Prevention
MetaPlate combines a glucose-response ML model, counterfactual meal optimization, and RAG-LLM to generate personalized recommendations that keep post-meal glucose ≤140 mg/dL, with dietitian ratings improving after prompt changes.