Education | MUST research on smart Covid diagnosis published in renowned journal

Chair Professor Zhang Kang

A research team at the Macau University of Science and Technology (MUST) has made significant progress on its research on smart diagnosis of Covid-19, and subsequently published the concerned paper in the international-level research journal Nature Biomedical Engineering.
The team, led by Chair Professor Zhang Kang, developed a smart system to diagnose Covid-19. The researchers studied 500,000 copies of chest computed tomography (CT) images and achieved last April over 90% success rate in diagnosing the disease. The system is ready to be in used in several international entities. According to Zhang, the chest X-ray system is both faster and more accessible than alternatives.
In addition, Zhang disclosed that the team studied a total of 145,000 copies of chest X-ray scans from 120,000 patients, all to develop a reliable artificial intelligence (AI) system to assist radiographers in differentiating more swiftly and accurately between Covid-19 and other types of pneumonia. The system can also help doctors diagnose other lung problems and evaluate the severity. He stressed that it can help identify diffuse pulmonary diseases, which are normally difficult to pinpoint by human eyes.
The automatic deep-learning system can be used for frontline diagnosis at A&E departments, outskirt areas or developing countries. It will also help hasten early intervention and provide crucial support to clinical decision-making.
According to the MUST, the mobility of the system makes it important in solving public health problems. Moreover, the source code and images are open to the public, MUST noted. AL

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