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Detection Of Covid-19 Using Cough Sounds

Smartphone-based COVID-19 Cough Detection with Artificial Intelligence - VIRUFY

Status
Active, not recruiting
Phases
Unknown
Study type
Interventional
Source
CTRI
Registry ID
CTRI/2022/03/041332
Enrollment
40000
Registered
2022-03-24
Start date
Unknown
Completion date
Unknown
Last updated
2024-10-14

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

Intervention1: Artificial intelligence Powered Mobile App: The clinical presentation of COVID-19 can be highly variable, however, a dry cough is a distinctive feature of most cases. Because COVID-19 c

Sponsors

The Covid Detection Foundation
Lead Sponsor
Christian Medical College
Collaborator

Eligibility

Inclusion criteria

Inclusion criteria: 1. All patients who have undergone rt-PCR test for COVID -19 prior to participation in the study. 2. Male or female participants 18 years or older 3. Pregnant women 4. Healthy Volunteers 5. Participants with comorbidities or other diseases resemblant of COVID-19 based on symptomatic profile at presentation. These conditions include, but are not limited to, ARDS, tuberculosis, viral pneumonitis, pertussis, hay fever, habit cough, and reflux. 6. Participants willing to provide a signed informed consent for voluntary participation in the study

Exclusion criteria

Exclusion criteria: 1. Impaired decision making capacity: inability to provide informed consent or to comply with study assessments (i.e. inadequate comprehension). 2. Cancer Subjects 3. Subjects at risk of severe adverse effects (such as coughing bouts due to asthma, COPD, or other conditions) through forcing a cough through participation in the study. 4. Laboratory Personnel 5. Employees Of Participating Sites 6. Prisoners

Design outcomes

Primary

MeasureTime frame
Clinically validated dataset needed to train and test a machine learning model that can accurately predict ones likelihood of having COVID-19 with a validated sensitivity of at least 75 and a specificity of at least 75 in a local populationTimepoint: 6 Months

Secondary

MeasureTime frame
The algorithms performance will be benchmarked against established diagnostic tests, including PCR and antigen testingTimepoint: 6 Months

Countries

Brazil, Colombia, India

Contacts

Public ContactAmit Gulrez

Christian Medical College

mariaghosh@gmail.com9878433394

Outcome results

None listed

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