Research on an Intelligent Health Recommendation System for Chronic Disease Comorbidity Integrating TCM

Research on an Intelligent Health Preservation Recommendation System for Chronic Disease Comorbidity Based on the Integration of Traditional Chinese Medicine Constitution Database and Multimodal Large Language Models

1. Construct a Traditional Chinese Medicine (TCM) constitution database, clarify the distribution patterns of TCM constitution in populations with comorbid "three-high" conditions (hypertension, hyperlipidemia, and hyperglycemia) and their associations with metabolic indicators. Establish a "constitution-comorbidity-metabolism" relationship model to provide a basis for personalized intervention and the development of an AI platform.
2. Develop the AI-HEALS system by integrating the TCM constitution database with multimodal large language models. This system will generate personalized intervention plans and provide intelligent interactive Q&A capabilities to enhance patient intervention adherence.
3. Evaluate the clinical application effectiveness of the AI-HEALS system, explore the relationship between changes in constitution and intervention outcomes, and validate the TCM intervention pathway of "regulating constitution to promote health." This will provide both theoretical and practical guidance for the dynamic regulation and precise intervention of TCM constitution.

This project combines Traditional Chinese Medicine (TCM) constitution theory with large language models (LLMs) through interdisciplinary integration, constructing a dynamically empowered intelligent health recommendation system for TCM. It promotes the deep integration of the "treatment based on constitution differentiation" concept with artificial intelligence. The significance of this research is mainly reflected in the following two aspects:

At the theoretical level, this study helps expand the knowledge representation and computational modeling methods of TCM constitution theory within the framework of modern artificial intelligence. It advances the application and transformation of the TCM concept of "preventive treatment" in big data and intelligent reasoning scenarios, provides new perspectives for research on the mechanisms linking TCM constitution and chronic disease comorbidities, and fosters cross-integration between TCM theoretical systems and modern medical information science.

At the practical level, the research relies on real clinical data and multimodal AI models to establish a structured, standardized TCM constitution database. It develops a health education system with individualized identification, intelligent recommendation, and dynamic intervention functions, suitable for personalized management and early warning in populations with chronic disease comorbidities. The project outcomes will help enhance individual health literacy and quality of life, alleviate the burden of chronic diseases, promote the practical application of TCM in primary healthcare services and digital medicine, and demonstrate significant social value and broad prospects for widespread adoption.

Inclusion Criteria:

Age ≥ 18 years; Clear diagnosis of hypertension, type 2 diabetes, and hyperlipidemia, and a comorbid condition involving all three diseases; Stable disease condition with no recent acute complications; Capable of completing questionnaires, and willing to provide informed consent to voluntarily participate in the study.

Exclusion Criteria:

Patients in the acute phase of the three high diseases (hypertension, diabetes, hyperlipidemia) or with severe complications (such as acute myocardial infarction or stroke); Patients with other major diseases that may affect constitution assessment or intervention implementation, such as malignant tumors, severe liver or kidney dysfunction, active tuberculosis, or mental illness; Patients who have received systematic Traditional Chinese Medicine treatment (e.g., herbal decoctions or acupuncture) within the past month, which may influence the initial assessment of constitution type; Pregnant or lactating women; Individuals unable to cooperate with measurements, with language communication barriers, or cognitive impairments; Patients participating in other interventional clinical studies.