A team from Tainan-based National Cheng Kung University (NCKU) that build an automatic pneumonia detection system has become one of the winners of an online competition organized by the WHO seeking solutions for challenges related to the COVID-19 pandemic, the university said on Monday.
The team, named “MedCheX” and headed by professor Chiang Jung-hsien (蔣榮先), created an electronic alert system that can detect pneumonia from chest X-rays and automatically alert doctors, which was on Friday last week announced as one of the 89 highlighted projects among 1,560 submissions in the COVID-19 Global Hackathon, the university said in a news release.
It is the only Taiwanese team to win the honor, it added.
Photo courtesy of National Cheng Kung University
Chiang said that the system was developed over the past two years with the aim of assisting doctors in diagnosing pneumonia more quickly.
The team created a UNet++ machine learning model that can automatically detect the presence of pneumonia.
Using this learning model, the system is able to automatically detect high-risk patients by scanning their chest X-rays to more quickly determine whether they have developed pneumonia, Chiang said.
If the test is positive, the doctor receives an e-alert via computer or mobile phone containing both the original scans and the detection results.
The team — which also features three graduate and doctoral students, as well as NCKU Hospital doctor Tsai Yi-shan (蔡依珊) — was able to build the system thanks to a cache of more than 1,000 chest X-rays from patients suspected of having pneumonia provided by the university’s Department of Medical Imaging, Chiang said.
The system has been deployed at the hospital and has greatly increased diagnosis efficiency.
Based on 1,400 images the system has scanned, it has achieved 92 percent accuracy in the detection of pneumonia symptoms, Chiang said.
Over the past three months, Chiang said that the system has also been used for early detection of potential COVID-19 cases.
The system only takes one second to determine if a chest X-ray of a patient needs further screening for the novel coronavirus, he said.
The team plans to include functions for other types of screening, such as computed tomography and magnetic resonance imaging scans, to provide doctors with even more accurate diagnostic information, he added.
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