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Researchers create ‘COVID computer’ to speed up diagnosis


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Researchers at the University of Leicester have developed a new AI tool that can detect COVID-19.

The software analyzes the chest CT scan and uses in-depth learning algorithms to accurately diagnose the disease. With an accuracy rate of 97.86%, it is currently the most successful COVID-19 diagnostic tool in the world.

Currently, the diagnosis of COVID-19 is based on nucleic acid testing, or PCR tests as it is commonly known. These examinations can produce false negatives and the results can also be affected by hysteresis — if the physical effects of a disease are late in their cause. AI, therefore, offers an opportunity for rapid screening and effective monitoring of COVID-19 cases on a large scale, reducing the burden on physicians.

Professor Yudong Zhang, Professor of Knowledge Discovery and Machine Learning at the University of Leicester says that their “research focuses on the automatic diagnosis of COVID-19 based on random graph neural network. The results show that our method to detect suspicious regions in Automatic breast images and make accurate predictions based on the representations.The accuracy of the system means that it can be used in the clinical diagnosis of COVID-19, which helps control the spread of the virus. We hope that, in the future, this type of technology will allow for automated computerized diagnosis without the need for manual intervention, in order to create a more intelligent, efficient health care service. “

Researchers are now further developing this technology in the hope that the COVID computer will eventually replace the need for radiologists to diagnose COVID-19 in clinics. The software, which can even be deployed on portable devices such as smart phones, will also be adapted and expanded to detect and diagnose other diseases (such as breast cancer, Alzheimer’s Disease, and cardiovascular diseases). .

The research was published in International Journal of Intelligent Systems.

Using convolutional neural network to analyze medical imaging

More information:
Siyuan Lu et al, NAGNN: Classification of COVID-19 based on neighbor known representation from deep graph neural network, International Journal of Intelligent Systems (2021). DOI: 10.1002/int.22686

Provided by the University of Leicester

Citation: Researchers create ‘COVID computer’ to facilitate diagnosis (2022, July 1) retrieved on July 1, 2022 from

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