Researchers create ‘COVID computer’ to speed up diagnosis

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Scientists at the University of Leicester have established a new AI software that can detect COVID-19.

The software analyzes upper body CT scans and utilizes deep learning algorithms to accurately diagnose the condition. With an accuracy rate of 97.86%, it can be now the most thriving COVID-19 diagnostic tool in the planet.

Presently, the diagnosis of COVID-19 is primarily based on nucleic acid screening, or PCR exams as they are normally regarded. These checks can create untrue negatives and final results can also be influenced by hysteresis—when the actual physical results of an disease lag driving their lead to. AI, consequently, features an option to speedily monitor and proficiently monitor COVID-19 situations on a substantial scale, decreasing the burden on medical doctors.

Professor Yudong Zhang, Professor of Understanding Discovery and Machine Mastering at the University of Leicester claims that their “analysis focuses on the computerized prognosis of COVID-19 dependent on random graph neural network. The effects confirmed that our approach can uncover the suspicious areas in the upper body pictures routinely and make accurate predictions based on the representations. The precision of the program suggests that it can be used in the medical analysis of COVID-19, which may well assistance to regulate the unfold of the virus. We hope that, in the future, this sort of technology will enable for automatic laptop prognosis devoid of the will need for handbook intervention, in purchase to make a smarter, efficient healthcare provider.”

Researchers will now even further build this engineering in the hope that the COVID pc may possibly ultimately exchange the have to have for radiologists to diagnose COVID-19 in clinics. The software, which can even be deployed in moveable devices this kind of as intelligent phones, will also be tailored and expanded to detect and diagnose other ailments (these as breast most cancers, Alzheimer’s Condition, and cardiovascular health conditions).

The investigation is revealed in the Worldwide Journal of Intelligent Programs.


Making use of convolutional neural networks to examine health-related imaging


Additional information:
Siyuan Lu et al, NAGNN: Classification of COVID‐19 based on neighboring informed illustration from deep graph neural community, Worldwide Journal of Smart Units (2021). DOI: 10.1002/int.22686

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University of Leicester


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Scientists create ‘COVID computer’ to speed up prognosis (2022, July 1)
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