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.
翻译:2019年新科罗纳病毒是一种非常严重的流行病,自2019年12月以来,已有数千甚至数百万人死亡。2020年3月,世界卫生组织将其定义为一种流行病。据说,这种病毒通常通过喷水或咳嗽或触摸受感染表面造成的滴滴传播。病毒的存在是通过实时反转转转酶聚合酶链反应(rRT-PCR)检测到的。此外,从鼻子或喉部抽取的吸盘显示是一种非常严重的流行病,自2019年12月以来,已有数千甚至数百万人死亡。此外,X光和CT成像方法也用于支持这一方法。由于人们知道 RRT-PCR测试的精确度敏感度很低,辅助诊断方法具有非常重要的位置。计算机辅助诊断和检测系统是在X光和CT图像的帮助下开发的。关于文献中检测COVID19的实时研究日日不断增多。在研究中,不同的批量(BH=3,10,30,40,和50)的准确值也被用于支持这一方法。在检测COVI的总体测试中,通过进行一项持续测试数据,对常规数据进行了深入的运行数据进行了深入分析,但进行PV19的运行数据进行了深入调查。