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Challenges

The medical diagnosis and evaluation using CT images are important to preventing and controlling the spread of the COVID-19. At the peak of the pandemic, the number of patients in hospital every day usually surpasses the maximum treatment capacity of the hospital. This means that not only are most departments overwhelmed, but this is hindered by traditional CT technology, which is not capable of providing fast and accurate diagnosis. Specifically, the system processes image browsing, compares historical images, and describes impact before generating an analysis report for radiologists. In normal settings, conventional diagnosis technology takes 15–20 minutes and delivers an accuracy rate up to 90%. However, due to the limited medical resources and heavy workload of doctors, this figure may decline in practice. Consequently, this impacts the future treatment of suspected cases, false negatives, and confirmed cases.

Solution

At this critical juncture, Huawei works with medical partners to find a way forward. In March 2020, Huawei and Advanced Global Solution (AGS), an Italian-based enterprise, jointly launched an AI-based medical image diagnosis system to supercharge the diagnosis and treatment for COVID-19. This diagnosis solution runs on the AI foundation and ultimate computing power of the Atlas 800 server and Atlas 300 inference card needed in a wide range of intelligent functions, such as intelligent CT image reading, automatic pneumonia classification, multi-color rendering of lesions, and intuitive comparison of baseline histograms.

Benefits

Combined with the AI image diagnosis system and the expertise of doctors, the solution quickly identifies the symptoms of patients with COVID-19 within 2 to 3 minutes, and evaluates the treatment effect with an accuracy rate over 98%. The fast and accurate diagnosis is crucial to the treatment of pandemics like the COVID-19. With the Atlas-based intelligent solution, doctors can determine the treatment scheme as soon as possible and allocate medical resources based on the severity of the disease, providing effective and timely treatment for patients in critical condition.

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