Respiratory diseases of a person including tuberculosis and Covid-19 can now be assessed using an artificial intelligence (AI) enabled technological system. Recently, the AI enabled technological system showed successful results after it was tried out at the Government Hospital for Chest and Communicable Diseases (GHCD). The hospital is attached to Andhra Medical College (AMC).
The cough sound-based AI technology will turn out to be of great help for doctors as well as for patients. Using the technology, doctors will be able to consume a lot of time.
As of now, pulmonary tests including CT scans, and X-rays, are depended on laboratories. However, a patient now can save both his money and time and doesn’t have to undergo those tests.
Also, for the extension of the technology for lung ailments such as bronchitis, asthma, and COPD, experiments are being made.
What C-CAMP associate programme lead DR Niranjan Joshi on the new technology
With a talk with Deccan Chronicle, the Centre for Cellular and Molecular Platforms associate programme lead Dr Niranjan Joshi said that in the battle to contain Covid-19 and TB, India and the UK came out with the latest innovation together.
How does it work?
Dr Joshi said that the technology allows a patient to cough on the mobile phone. Then the AI receives an accurate medical assessment of their ailments. This further allow patients and doctors to figure out whether the patient needs more testing to monitor the case or not. This procedure saves a lot of time and money.
British deputy high commissioner for Telangana and AP Dr Andrew Fleming at GHCCD witnessed the live performance of the new technology. On which he said that after UK-India Astra-Zeneca vaccine collaboration to contain Covid-19, this is another success. He himself took the test and got his results within a couple of minutes.
Joshi also discussed about the current Covid and TB scenario in India. He said that in 2019, 2.64 million TB cases were recorded and 75,000 plus deaths occurred. Lager percentage of cases were from underdeveloped remote areas where there was no proper health service.
