AI could revolutionize TB care by predicting who needs shorter treatment

NCT ID NCT07611695

Not yet recruiting Knowledge-focused Sponsor: Huashan Hospital Source: ClinicalTrials.gov ↗

First seen Jun 25, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This study will use artificial intelligence to analyze data from over 31,000 tuberculosis patients. The goal is to create a system that helps doctors decide which patients can be cured with a short treatment course and which need longer therapy. The AI will be tested to see if it can improve cure rates and personalize care for each patient.

What this could mean

Our plain-language read of the trial. This is informational only — not medical advice or a prediction.

What this could lead to: If successful, this AI system could help doctors quickly identify which TB patients need shorter or longer treatment, leading to more personalized and effective care.
What could go wrong: This is an observational study, not a treatment trial, so it won't directly test a new drug or cure. The AI model may not work as well in real-world settings or for all patient groups.

This is an AI summary of the original study and may miss details. Read our disclaimer.

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Conditions

The condition(s) this trial relates to.

active tuberculosis pulmonary tuberculosis tuberculosis

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

PULMONARY TUBERCULOSIS TUBERCULOSIS (TB) TUBERCULOSIS ACTIVE

Contacts and locations

Locations

Huashan Hospital Affiliated to Fudan University

Shanghai, 210000, China
Hunan Chest Hospital

Changsha, Hunan, China

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