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NCT Number: NCT06525025

Building a Traditional Chinese Medicine Clinical Diagnosis and Treatment Database

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.

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Key information

Conditions

Medicine, Chinese Traditional Artificial Intelligence

Age range

18 year–85 year

Sex eligibility

All sexes

Study type

Observational

About this study

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.

Who can participate

Healthy volunteers accepted: Yes

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

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.

Treatment and study plan

Observational study, non intervention

Other

Observational study, non intervention

Primary outcomes

  1. Development of a tongue image-based machine learning tool

    Time frame: 20 months

    • It is anticipated to enroll 50,000 samples to establish a Traditional Chinese Medicine (TCM) tongue appearance database.
    • The tongue images will undergo quality selection and preprocessing.
    • The tongue images will be manually annotated, with 40% allocated to the training group and 60% to the testing group.
    • For the training group: A TCM tongue appearance model will be constructed based on the manually annotated tongue images.
    • For the testing group: The TCM tongue appearance model will be used to interpret the tongue images.
    • 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

  1. TCM Constitution Multimodal Model

    Time frame: 20 months

    • It is projected to include 20,000 samples to construct a Traditional Chinese Medicine (TCM) constitution database.
    • Of these, 15,000 samples will complete the TCM constitution survey questionnaire and have their tongue and facial diagnosis data collected.
    • Based on the data from step 2, a multimodal TCM constitution assessment model will be constructed.
    • An additional 5,000 samples will be tested, first by completing the multimodal TCM constitution assessment model, and then the TCM constitution survey questionnaire.
    • Analyze the consistency between the readings of the TCM constitution assessment model and the results from the TCM constitution survey questionnaire generation, and treatment plan recommendations, prepare in advance for optimizing interactive large-scale TCM models.

Other outcomes

  1. Traditional Chinese Medicine (TCM) Doctor-Patient Dialogue Database

    Time frame: 20 months

    • It is anticipated to include 10,000 samples to construct a Traditional Chinese Medicine (TCM) doctor-patient dialogue database.
    • Optimize the TCM large model, which mainly includes the following aspects: a Q&A system, assistance in medical record generation, and recommendation of diagnosis and treatment plans.

Study contacts

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

Yulong Zhang, Doctor

CONTACT

[email protected]

18810550602

Sponsors and collaborators

Lead sponsor

Fifth Affiliated Hospital, Sun Yat-Sen University

Other

Registry information

Official study title

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

Important dates

Study start
2024
Primary completion
2024
Study completion
2026
First posted
Jul 29, 2024
Registry last updated
Jul 29, 2024

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.

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