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Real-World Data Linkage Research Platform

NCT07635355 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 300000

Last updated 2026-06-09

No results posted yet for this study

Summary

This study aims to address the lack of intelligent governance tools in clinical data management to promote efficient governance and secure sharing of real-world health data. To achieve this, a self-adaptive, automated governance intelligent agent will be developed based on a High-Order Programming (HOP) architecture, integrating Large Language Models (LLMs) and deep learning techniques. The agent will continuously monitor and correct data quality issues in real time, improving data accuracy and usability.

In parallel, the project will establish a trusted data-sharing framework by integrating AI Confidential Computing (AICC) with Trusted Data Matrix (TDM) technologies. This framework will enable secure, real-time cross-institutional data exchange and collaborative computation while protecting sensitive information.

Overall, the study aims to transform fragmented clinical data into high-quality, standardized, and securely accessible resources, thereby facilitating the circulation of data value and advancing collaborative medical research.

Conditions

Interventions

OTHER

This is an observational study. No intervention will be applied.

This is an observational study. No intervention will be applied.

Sponsors & Collaborators

  • Shenzhen Third People's Hospital

    collaborator OTHER

  • First Affiliated Hospital Xi'an Jiaotong University

    collaborator OTHER

  • Beijing Friendship Hospital

    lead OTHER

Principal Investigators

  • Yuanyuan Kong · Beijing Friendship Hospital

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2026-05-30
Primary Completion
2028-12-31
Completion
2030-12-31

Countries

  • China

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07635355 on ClinicalTrials.gov