The Coronavirus Disease 2019 (COVID-19) has spread globally and caused serious damages. Chest X-ray images are widely used for COVID-19 diagnosis and Artificial Intelligence method can assist to increase the efficiency and accuracy. In the Challenge of Chest XR COVID-19 detection in Ethics and Explainability for Responsible Data Science (EE-RDS) conference 2021, we proposed a method which combined Swin Transformer and Transformer in Transformer to classify chest X-ray images as three classes: COVID-19, Pneumonia and Normal (healthy) and achieved 0.9475 accuracy on test set.
翻译:2019年科罗纳病毒疾病(COVID-19)已遍及全球,造成严重损害;胸X射线图像被广泛用于COVID-19诊断和人工智能方法,有助于提高效率和准确性;在2021年 " 胸XR COVID-19在 " 负责任的数据科学伦理和解释(EE-RDS) " 会议上,我们提出了一个方法,将变异器中的Swin变异器和变异器合在一起,将胸X射线图像分为三类:COVID-19、肺炎和正常(健康),并在测试集上达到0.9475的精确度。