Andhra Medical Faculty tries out AI platform for lung well being evaluation

Andhra Medical Faculty, one in all India’s oldest medical colleges, has began attempting out a brand new AI platform that assesses sufferers’ lung well being, together with those that have contracted COVID-19. 


The know-how being trialled was developed by Telangana-based Salcit Applied sciences. Referred to as Swaasa, the AI platform makes use of machine studying to carry out an audiometric evaluation of cough sounds, together with temperature, oxygen saturation, signs. 

Swaasa is being examined within the major healthcare setting on the Rural Well being Coaching Centre in Simhachalam. Round 2,000 sufferers are focused to partake within the examine, which can run over a six-month interval.


In an interview with Instances of India, Dr P.V. Sudhakar, principal of AMC, stated current strategies of analysis comparable to x-ray, CT scan and different pulmonary assessments require a laboratory setup, which may be “costly and time-consuming”. “Furthermore, they don’t seem to be out there in all rural and tribal areas,” he added.

Dr Devi Madhavi, head of AMC’s Division of Group Medication, additionally stated within the information report that the Swaasa will probably be “extremely helpful in figuring out the suitable subsequent intervention”, because the gadget helps in screening and figuring out whether or not a lung situation is attributable to airways or lung parenchyma or pleura.

In line with its web site, Salcit goals to exchange spirometry, the most typical, easy lung diagnostic check, with its AI software. 


Like Salcit, researchers on the Massachusetts Institute of Expertise have developed a low-cost resolution for diagnosing COVID-19 that may be deployed in areas the place complete diagnostic testing is unavailable. Final yr, they launched an AI software that additionally analyses coughs to find out whether or not or not a affected person is optimistic for COVID-19. 

The researchers collected over 70,000 audio recordings of individuals’s coughs by a web site and used these information to develop, prepare and validate a mannequin that checks particular acoustic biomarkers associated to muscular degradation, vocal twine modifications, sentiment or temper modifications and modifications within the lungs or respiratory tract. 

After testing, the software was discovered to have 97.1% accuracy, 98.5% sensitivity and 94.2% specificity in detecting COVID-19 optimistic circumstances.

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