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Clinical Trials/NCT06525025
NCT06525025
Not yet recruiting
Not Applicable

Building a Traditional Chinese Medicine Clinical Diagnosis and Treatment Database: A Prospective Multicenter Cross-Sectional Study

Fifth Affiliated Hospital, Sun Yat-Sen University0 sites80,000 target enrollmentAugust 1, 2024

Overview

Phase
Not Applicable
Intervention
Not specified
Conditions
Medicine, Chinese Traditional
Sponsor
Fifth Affiliated Hospital, Sun Yat-Sen University
Enrollment
80000
Primary Endpoint
Development of a tongue image-based machine learning tool
Status
Not yet recruiting
Last Updated
last year

Overview

Brief Summary

Collecting Traditional Chinese Medicine (TCM) clinical diagnosis and treatment data, including doctor-patient dialogues, tongue diagnosis, facial diagnosis, and TCM constitution information, to construct databases for tongue diagnosis, TCM constitution, and doctor-patient dialogues. Based on artificial intelligence technology, engage in research related to the standardization and intelligentization of TCM.

Detailed Description

The technological principles of large language models align with the empirical medical principles of Traditional Chinese Medicine (TCM), and the rise of large model technology can greatly promote the progress of TCM. However, there is currently a lack of clinical diagnosis and treatment databases with TCM characteristics for training TCM artificial intelligence(AI) large models. At present, a large-scale tongue image database has not yet been established for modeling common TCM tongue appearances, thereby ensuring the accuracy and consistency of TCM diagnosis and promoting the objective standardization of TCM diagnostic development. Considering the feedback from the subjects in clinical work that the TCM constitution survey questionnaire has a large volume, takes a long time, and has certain subjective issues, we plan to carry out a large-scale clinical observational study to optimize the process of TCM constitution identification. Traditional Chinese Medicine (TCM) doctor-patient dialogues and medical record writing are essential entities generated during the TCM diagnosis and treatment process. Assisting in consultation, medical record generation, and treatment plan recommendations based on doctor-patient dialogues have significant clinical and research value. Therefore, we plan to collect a large number of doctor-patient dialogues and outpatient medical records to construct a doctor-patient dialogue database, preparing in advance for optimizing interactive large-scale TCM models. In summary, the research on constructing a TCM clinical diagnosis and treatment database has important clinical and scientific research value. This will help to improve the standardization and normalization of TCM diagnosis and treatment, and also support the modernization and internationalization of TCM. By applying big data analysis and artificial intelligence technology, it is possible to delve deeper into TCM diagnosis and treatment information, providing richer and more accurate data resources for clinical decision-making and scientific research exploration in TCM.

Registry
clinicaltrials.gov
Start Date
August 1, 2024
End Date
August 15, 2026
Last Updated
last year
Study Type
Observational
Sex
All

Investigators

Sponsor
Fifth Affiliated Hospital, Sun Yat-Sen University
Responsible Party
Sponsor

Eligibility Criteria

Inclusion Criteria

  • People who come to the hospital for physical examination and medical treatment;
  • Participants voluntarily participate in the study.

Exclusion Criteria

  • Subjects with difficulty in tongue extension, communication, etc. who cannot cooperate with data collection;
  • The researchers determined that there were other factors that may have forced the subjects to terminate the study.

Outcomes

Primary Outcomes

Development of a tongue image-based machine learning tool

Time Frame: 20 months

1. It is anticipated to enroll 50,000 samples to establish a Traditional Chinese Medicine (TCM) tongue appearance database. 2. The tongue images will undergo quality selection and preprocessing. 3. The tongue images will be manually annotated, with 40% allocated to the training group and 60% to the testing group. 4. For the training group: A TCM tongue appearance model will be constructed based on the manually annotated tongue images. 5. For the testing group: The TCM tongue appearance model will be used to interpret the tongue images. 6. Analyze the consistency between the tongue appearance interpretations by the model built from the training group and the readings by TCM physicians for the testing group's tongue images.

Secondary Outcomes

  • TCM Constitution Multimodal Model(20 months)

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