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NCT Number: NCT07308366

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

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.

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Key information

Sex eligibility

All sexes

Study type

Observational

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

Multimodal AI Models

Other

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.

Primary outcomes

  1. Traditional Chinese Medicine (TCM) Constitution Database

    Time frame: Observation period: 3 years

    Develop the AI-HEALS intelligent intervention platform, equipped with functions such as constitution identification, intelligent recommendations, and interactive Q&A, achieving a Q&A accuracy rate of over 90%.

Study contacts

Contact information is provided by the study sponsor or research team.

qingqing liu

CONTACT

[email protected]

13858089867

yibo wu

CONTACT

[email protected]

13758089867

Sponsors and collaborators

Lead sponsor

The Fourth Affiliated Hospital of Zhejiang University School of Medicine

Other

Registry information

Official study title

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

Important dates

Study start
2025
Primary completion
2028
Study completion
2028
First posted
Dec 29, 2025
Registry last updated
Dec 29, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.