In order to process the CT images of suspected Covid-19 cases in a timely manner, Alibaba DAMO Academy and Alibaba Cloud have jointly developed a new set of AI diagnostic technologies for clinical use. The AI system can accurately analyze the CT images within 20 seconds, with an accuracy rate of 96%. Zhengzhou’s main Covid-19 hospital, launched on Feb 16, has introduced this AI algorithm to aid clinical diagnosis. Zhengzhou is the capital of Henan Province, one of the provinces with the highest cases of Covid-19 outside of Hubei Province.
Nucleic acid testing has been recognized as the main reference standard for the diagnosis of Covid-19 as evidence of pathogenicity. With the accumulation of clinical diagnostic data, the imaging big data features of Covid-19 gradually becoming clearer, the CT-imaging diagnosis results become more and more important. According to the fifth edition of the diagnosis and treatment plan announced by the National Health and Health Commission, the clinical diagnosis does not need to rely on nucleic acid test results. The clinical diagnosis results of the CT images can be used as the criterion for identifying new Covid-19 cases.
The imaging features of the CT chest radiographs of patients with Covid-19 show subtle changes in one or both lungs with patchy or segmental ground glass densities. The number of CT images for one Covid-19 patient is about 300, which puts great pressure on the doctor’s clinical diagnosis. The doctor’s visual analysis of the CT images of one case could take about 5 to 15 minutes.
The medical AI team of Alibaba DAMO Academy based their AI system research on the latest diagnosis and treatment programs, data sampling of more than 5000 cases, as well as Zhong Nanshan and other authoritative teams’ published papers on the clinical characteristics of patients with Covid-19 to come up with a new AI algorithm model to expedite the diagnosis of the virus.
According to reports, through NLP natural language processing of retrospective data and the use of CNN convolutional neural networks to train CT image recognition networks, AI can quickly identify the difference between Covid-19 images and ordinary viral pneumonia images, with a final recognition accuracy rate of 96%. AI takes less than 20 seconds to identify each case on average, which can effectively reduce the pressure on doctors. In addition, AI can also directly calculate the proportion of the lesion site on a patient’s lungs, thereby quantifying the severity of the cases to greatly improve the efficiency of clinical diagnosis.
Editor’s note: This is part of our ongoing Tech for Good series, highlighting how Chinese tech companies are helping fight the impact of the coronavirus. This was originally written by Steven Lee, a writer for our sister site, TechNode Chinese. Read the Chinese version here.