Sydney: The Australian computer scientists have developed a novel Artificial Intelligence-based model that can hear the effects of Covid-19 in the sound of a forced cough, even when people are asymptomatic.
This advanced method can pave the way for detecting the infectious disease via diagnostic mobile phone apps,suggests study.
Apparently, many crowdsourcing platforms have been trying to gather respiratory sound audios from both healthy and Covid-19 positive groups for research purposes during the pandemic.
However, A team of researchers from RMIT University finally made it by accessing datasets from two of these platforms -- Covid-19 Sounds App and COSWARA -- to train the algorithm using contrastive self-supervised learning, a method by which a system works independently to encode what makes two things similar or different.
With further development, their algorithm could power a diagnostic mobile phone app, said lead author Hao Xue, Research Fellow in RMIT's School of Computing Technologies.
"We've overcome a major hurdle in the development of a reliable, easily-accessible and contactless preliminary diagnosis tool for Covid-19," said Xue, Research Fellow in RMIT's School of Computing Technologies.
Xue said the method they developed could also be extended for other respiratory diseases like tuberculosis.
According to co-author Professor Flora Salim, previous attempts to develop this type of technology, like those at MIT and Cambridge, relied on huge amounts of meticulously-labeled data to train the AI system."The annotation of respiratory sounds requires specific knowledge from experts, making it expensive and time-consuming, and involves handling sensitive health information," she said.
"What's most exciting about our work is we have overcome this problem by developing a method to train the algorithm using unlabelled cough sound data. This can be acquired relatively easily and at a larger scale from different countries, genders and ages," Salim added.