Peter the GreatSt. Experts from St. Petersburg Polytechnic University (SPbPU) have developed a powerful neural network that can accurately detect the presence of COVID-19 in X-ray and CT images of the lungs. According to the university, this neural network achieves an impressive accuracy rate of 99.23%. At the same time, the image analysis process takes much less time than PCR tests and allows early detection of disease symptoms.
X-rays and CT scans of the lungs are an important additional tool in diagnosing COVID-19 and help rule out pneumonia associated with this virus. However, the interpretation of these images requires highly qualified experts. To facilitate this process and increase the accuracy of diagnoses, researchers have developed a neural network that can automatically detect signs of COVID-19 in CT images.
This neural network can significantly speed up and improve the diagnostic process, which can reduce the burden on medical personnel. The scientists trained the neural network using comprehensive computed tomography images of the lungs obtained from patients with different types of pneumonia. The results showed that this neural network has the potential to quickly and accurately diagnose COVID-19 from medical images.
Source: Ferra
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