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Role of cough and voice analysis using artificial intelligence in the management of COVID 19 patients

Role of novel non-invasive cardiopulmonary assessments in early detection, triaging and predicting prognosis of COVID 19 patients

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2020/07/026677
Enrollment
250
Registered
2020-07-19
Start date
Unknown
Completion date
Unknown
Last updated
2021-11-24

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

Conditions

Health Condition 1: B972- Coronavirus as the cause of diseases classified elsewhere

Interventions

None listed

Sponsors

Gnaneswar Atturu
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: 1.Confirmed COVID 19 positive patients (both symptomatic and asymptomatic) 2.Suspected but not confirmed COVID 19 patients 3.Contacts of confirmed COVID 19 patients 4.Persons with previous co-morbidities will also be considered

Exclusion criteria

Exclusion criteria: 1. Persons who refuse to give consent 2. Persons who canâ??t cough or record a sentence 3. Patients who are on ventilator support (at the time of recruitment)

Design outcomes

Primary

MeasureTime frame
collecting the necessary acoustic samples from COVID 19 patients and healthy volunteers that can be used to build a machine learning model and understand the acoustic patterns.Timepoint: 3 months—

Secondary

MeasureTime frame
usability of mobile application in early detection, triaging and predicting prognosis of COVID 19 patientsTimepoint: 3 months—

Countries

India

Contacts

Public ContactGnaneswar Atturu

CARE Hospitals

dr.gnaneswar.atturu@carefamily.in7674893748

Outcome results

None listed

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