Despite the introduction of vaccines, Coronavirus disease (COVID-19) remains a worldwide dilemma, continuously developing new variants such as Delta and the recent Omicron. The current standard for testing is through polymerase chain reaction (PCR). However, PCRs can be expensive, slow, and/or inaccessible to many people. X-rays on the other hand have been readily used since the early 20th century and are relatively cheaper, quicker to obtain, and typically covered by health insurance. With a careful selection of model, hyperparameters, and augmentations, we show that it is possible to develop models with 83% accuracy in binary classification and 64% in multi-class for detecting COVID-19 infections from chest x-rays.

翻译：尽管引入了疫苗,但科罗纳病毒(科罗纳病毒(COVID-19)仍然是全球的两难境地,不断开发新的变异体,如三角洲和最近的奥微生物。目前的检测标准是通过聚合酶链反应(PCR)进行,然而,多氯联苯的检测成本可能很高、速度缓慢和(或)对许多人来说是无法进入的。另一方面,自20世纪初以来,X光被轻易使用,而且比较便宜、更快地获得,而且通常由医疗保险覆盖。通过仔细选择模型、超光谱和扩增,我们表明有可能开发出在二进制分类中精确度为83%的模型和在多级中精确度为64%的模型,用于检测胸X光的COVID-19感染。