Currently, the diagnosis of Covid is based on nucleic acid testing or PCR tests, as they are commonly known. These tests can produce false negatives, and results can also be affected by hysteresis – when the physical effects of an illness lag behind their cause.
AI, therefore, offers an opportunity to rapidly screen and effectively monitor Covid cases on a large scale, reducing the burden on doctors.
“Research focuses on the automatic diagnosis of Covid-19 based on random graph neural networks. The results showed that our method could automatically find the suspicious regions in the chest images and make accurate predictions based on the representations,” said Yudong Zhang, Professor of Knowledge Discovery and Machine Learning at the varsity.
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“The accuracy of the system means that it can be used in the clinical diagnosis of Covid-19, which may help to control the spread of the virus. We hope that, in the future, this type of technology will allow for automated computer diagnosis without the need for manual intervention to create a smarter, efficient healthcare service,” Zhang said.
The research is published in the International Journal of Intelligent Systems.
Researchers will further develop this technology in to hope that the Covid computer may eventually replace the need for radiologists to diagnose Covid in clinics.
The software, which can even be deployed in portable devices such as smartphones, will be adapted and expanded to detect and diagnose other diseases (such as breast cancer, Alzheimer’s Disease, and cardiovascular diseases).
Source: IANS
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