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Testing an AI System to Detect Tuberculosis Using Cough Sounds and Symptoms

Diagnostic accuracy of an AI based screening system for detection of pulmonary tuberculosis using cough sounds and symptoms - NIL

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2025/03/081842
Enrollment
1260
Registered
2025-03-06
Start date
Unknown
Completion date
Unknown
Last updated
2025-04-07

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Health Condition 1: A159- Respiratory tuberculosis unspecified

Interventions

Intervention1: NIL: NIL

Sponsors

AIIMS Delhi /Lords Education & Health Society
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: Age greater than 18 years Cough of any duration Willing to give consent

Exclusion criteria

Exclusion criteria: Individuals less than 18 years of age Patients unwilling to give consent Patients requiring emergency management (clinically unstable) Pregnant women, patients with pacemakers etc. among whom X-ray is prohibited Patients currently on antitubercular therapy

Design outcomes

Primary

MeasureTime frame
To evaluate the sensitivity, specificity, and accuracy of the AI solution in the detection of patients with TB, using cough sounds, comorbidity and symptom historyTimepoint: at 6 months and at 12 months (or till 126 confirmed TB positive patients are found; whichever is earlier)—

Secondary

MeasureTime frame
NILTimepoint: NIL—

Countries

India

Contacts

Public ContactHarsh Shukla

Dept. of Medicine, AIIMS, New Delhi

neerajnischal@gmail.com9811484060

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Feb 4, 2026