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Artificial Intelligence-driven Tuberculosis Landscape Analysis & Stratification Research

NCT07611695 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 31600

Last updated 2026-05-28

No results posted yet for this study

Summary

The goal of this observational study is to establish and validate a comprehensive AI-driven clinical decision support system (AI-CDSS) in whole-chain management for pulmonary tuberculosis (TB) patients. The main question it aims to answer is:

How is the predictive performance of this system in terms of multiple key links during TB diagnosis and treatment? Can real-world benefits be derived from this system? This AI framework supports clinicians in making smarter decisions, ultimately improving cure rates and ensuring that every patient receives the most effective, personalized care possible.

Conditions

  • Pulmonary Tuberculosis
  • Tuberculosis (TB)
  • Tuberculosis Active

Sponsors & Collaborators

  • The Hong Kong Polytechnic University

    collaborator OTHER

  • Huashan Hospital

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-06-01
Primary Completion
2027-12-31
Completion
2028-06-30

Countries

  • China

Study Locations

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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 NCT07611695 on ClinicalTrials.gov