Screening COVID-19 by Swaasa AI Platform using cough sounds: A cross-sectional study

Abstract

The Advent of Artificial Intelligence (AI) has led to the use of auditory data for detecting various diseases, including COVID-19. SARS-CoV-2 infection has claimed more than 6 million lives till date and hence, needs a robust screening technique to control the disease spread. In the present study we developed and validated the Swaasa AI platform for screening and prioritizing COVID-19 patients based on the signature cough sound and the symptoms presented by the subjects. The cough data records collected from 234 COVID-19 suspects were subjected to validate the convolutional neural network (CNN) architecture and tabular features-based algorithm. The likelihood of the disease was predicted by combining the final output obtained from both the models. In the clinical validation phase, Swaasa was found to be 75.54% accurate in detecting the likely presence of COVID-19 with 95.45% sensitivity and 73.46% specificity. The pilot testing of Swaasa was carried out on 183 presumptive COVID subjects, out of which 82 subjects were found to be positive for the disease by Swaasa. Among them, 58 subjects were truly COVID-19 positive, which corresponds to a Positive Predictive Value of 70.73%. The currently available rapid screening methods are very costly and require technical expertise, therefore a cost effective, remote monitoring tool would be very beneficial for preliminary screening of the potential COVID-19 subject.

Competing Interest Statement

The authors have declared no competing interest.

Clinical Protocols

http://ctri.nic.in/Clinicaltrials/showallp.php?mid1=60601&EncHid=&userName=Swaasa%20Artificial%20Intelligence%20Platform%20for%20detecting%20likely%20presence%20of%20Pulmonary%20Tuberculosis

Funding Statement

This study is supported by the UK Government (British High Commission, New Delhi).

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

Ethics committee/IRB of Andhra Medical College gave ethical approval for this work.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.

Yes

Data Availability

All data produced in the present study are available upon reasonable request to the authors

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