不同批量参数对预测COVID19病例的影响
Effect of Different Batch Size Parameters on Predicting of COVID19 Cases
摘要：
2019新型冠状病毒又称COVID 19，是一种非常严重的疫情，自2019年12月以来，已经导致数千人甚至数百万人死亡。世界卫生组织于二零二零年三月将其定义为大流行病。据称，这种病毒通常通过打喷嚏或咳嗽引起的飞沫传播，或通过接触受感染的表面传播。病毒的存在是通过实时逆转录酶聚合酶链反应（rRT-PCR）检测的帮助下，从鼻子或喉咙拭子。此外，X射线和CT成像方法也被用来支持这种方法。由于已知rRT-PCR检测的准确性灵敏度较低，因此辅助诊断方法具有非常重要的地位。计算机辅助诊断和检测系统特别是在X射线和CT图像的帮助下开发。文献中关于COVID 19检测的研究日益增多。在本研究中，使用属于4个不同类别（病毒性肺炎、COVID 19、正常、细菌性肺炎）的数据，研究了不同批量（BH=3、10、20、30、40和50）参数值对其检测COVID 19和其他类别性能的影响。该研究使用预先训练的ResNet 50卷积神经网络进行。根据获得的结果，他们对训练和测试数据的表现非常接近。然而，观察到随着批量值的增加，检测数据中的稳态延迟。BH = 3时COVID 19检测的最高值为95.17%，而BH = 20时的总体准确度值为97.97%。根据研究结果，可以说批量值不会显著影响整体性能，但批量值的增加会延迟获得稳定结果。
英文摘要：
The new coronavirus 2019, also known as COVID19, is a very serious epidemic that has killed thousands or even millions of people since December 2019. It was defined as a pandemic by the world health organization in March 2020. It is stated that this virus is usually transmitted by droplets caused by sneezing or coughing, or by touching infected surfaces. The presence of the virus is detected by real-time reverse transcriptase polymerase chain reaction (rRT-PCR) tests with the help of a swab taken from the nose or throat. In addition, X-ray and CT imaging methods are also used to support this method. Since it is known that the accuracy sensitivity in rRT-PCR test is low, auxiliary diagnostic methods have a very important place. Computer-aided diagnosis and detection systems are developed especially with the help of X-ray and CT images. Studies on the detection of COVID19 in the literature are increasing day by day. In this study, the effect of different batch size (BH=3, 10, 20, 30, 40, and 50) parameter values on their performance in detecting COVID19 and other classes was investigated using data belonging to 4 different (Viral Pneumonia, COVID19, Normal, Bacterial Pneumonia) classes. The study was carried out using a pre-trained ResNet50 convolutional neural network. According to the obtained results, they performed closely on the training and test data. However, it was observed that the steady state in the test data was delayed as the batch size value increased. The highest COVID19 detection was 95.17% for BH = 3, while the overall accuracy value was 97.97% with BH = 20. According to the findings, it can be said that the batch size value does not affect the overall performance significantly, but the increase in the batch size value delays obtaining stable results.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
