Back to search

Article

Hybrid Artificial Intelligence and Large Language Model-Based Digital Health Platform for Personalized Diabetes Self-Management and Patient Engagement

2026-07-31

Abstract excerpt

<h4>Background: </h4> /Objectives: Sustained diabetes self-management remains one of the greatest challenges in chronic disease care because most existing healthcare solutions rely on generic education, static learning resources, or simple data logging that fail to adapt to individual patient needs and maintain long-term engagement. This study introduces AIDCare, an artificial intelligence (AI)-driven diabetes sel...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
d6053018-fefd-59bb-9b36-c266dcc96b27
DOI
10.20944/preprints202607.2337.v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Hybrid Artificial Intelligence and Large Language Model-Based Digital Health Platform for Personalized Diabetes Self-Management and Patient EngagementDOI 10.20944/preprints202607.2337.v1
NutriSteppe-AI: Development, Architecture, and Explainable Design of a Large Language Model–Driven Chatbot for Personalized Health Menu GenerationSemantic proximity
Glucobuddy: Detecting Diabetes Risk Using Machine LearningSemantic proximity
Exploring the Potential of Large Language Models in Personalized Diabetes Treatment StrategiesSemantic proximity
Artificial Intelligence in Dietary Recommendations for Type 1 Diabetes: Evaluating the Performance of ChatGPT-4o, Bing AI, and Bard AISemantic proximity
ChatGPT with Mixed-Integer Linear Programming for Precision Nutrition RecommendationsSemantic proximity
Exploring the Potential of Large Language Models in Personalized Diabetes Treatment StrategiesSemantic proximity
How Can I Stay Healthy? – Benchmarking Large Language Models for Personalized and Biomarker-Based Intervention RecommendationsSemantic proximity
In-depth expansion of Internet hospital services and multi-dimensional exploration of AI-empowered medical servicesSemantic proximity
Human-in-the-Loop AI Digital Twin to Extend Virtual Precision Diabetes Care Between Visits: Results From a Randomized Clinical TrialSemantic proximity
Response consistency of ChatGPT-4o for Type 2 Diabetes Nutrition and Physical-activity Recommendations: A Pilot NLP-based Assessment of GPT outputsSemantic proximity
Trust in large language model-based solutions in healthcare among people with and without diabetes: a cross-sectional survey from the Health in Central Denmark cohortSemantic proximity
Evaluating the Effectiveness and Safety of Large Language Model in Generating Type 2 Diabetes Mellitus Management Plans: A Comparative Study with Medical Experts Based on Real Patient RecordsSemantic proximity
Select a neighboring publication to make it the new centre.