Artificial Intelligence-driven Tuberculosis Landscape Analysis & Stratification Research

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.

NCT Number	NCT07611695
Lead Sponsor	Huashan Hospital Collaborators: The Hong Kong Polytechnic University
Conditions	Pulmonary Tuberculosis, Tuberculosis (TB), Tuberculosis Active
Enrollment	31,600 participants
Start Date	2026-06-01
Primary Completion	2027-12-31 (estimated)
Study Completion	2028-06-30 (estimated)
Updated on ClinicalTrials.gov	2026-05-28