Web server self-examination for detection of COVID-19 cases with fuzzy classifiers using chest X-ray image

The coronavirus has spread fast resulting in a worldwide pandemic. Early discovery of positive patients is critical in preventing the pandemic from spreading further, leading to the development of diagnostic technologies that provide rapid and reliable responses for COVID-19 detection. Previous research has shown that chest x-rays are an essential tool for the detection and diagnosis of sirivanoroC (COVID-19) patients. A radiological finding known as ground-glass opacity (GGO), which causes color and texture changes, was discovered in the lung of a person with COVID-19 as a consequence of x-ray tests. An automatic method to assist radiologists is required due to the carelessness of radiologists who work a long time and misdiagnosis resulting in the confusion of findings with different diseases, in this study, were described a new technique to help us with the early diagnosis of COVID-19 using x-rays that is based on fuzzy classification. The skewness, kurtosis, and average statistical features of x-rays of patients in two classes, COVID and Normal, are calculated in the suggested method, and the value ranges for both classes are identified. In the building of a fuzzy logic classifier, three statistical characteristics and value ranges are used as membership functions. The suggested solution, which uses a user-friendly interface, allows for quick and accurate COVID vs Normal (binary classification). Experiments show that our method has a lot of promise for radiologists to validate their initial screening and enhance early diagnosis, isolation, and therapy, which helps prevent infection and contain the pandemic. © 2023 Author(s).

Building Predictive Model of Covid 19 Quarantine Impact on the Purchase of Environmentally Green Products by Using J48 and LMTAlgorithms

When COVID 19 pandemic appeared, World Health Organization officially announced on January 30, 2020, that the outbreak of the virus constituted a health emergency, and most countries of the world announced a quarantine of all citizens as one of the precautionary to limit the epidemic spread. The Kingdom of Saudi Arabia is one of the countries that announced quarantine, which had an impact on all aspects of life. This study is related to the impact of quarantine on the purchase of green products and effects on the environment, that by using machine learning algorithms. J48 and ML algorithms were used to Build a predictive model to estimate the effect of the quarantine for covid 19 on the purchase of environmentally friendly food products that in Zulfi region of the Kingdom of Saudi Arabia and found that J48 algorithm have highest performance compared to LMT algorithm.

Coronavirus disease-19 and dentistry: A review

Novel coronavirus (nCoV) is a novel form of virus with a new strain identified recently in humans. Common clinical signs and symptoms primarily consist of fever, cough, and breathing difficulties. In severe cases, it can results in pneumonia, severe acute respiratory syndrome, kidney failure, and even death. It is important to follow all infection control measures in prevention of the nCoV from spreading and controlling the epidemic situation. The risk of cross infection can be high between dental practitioners and patients due to the features of dental clinical settings. Here, we are summarizing the nCoV related information and infection control measures to be followed in dental practice. © 2020 Fareedi Mukram Ali, Kishor Patil, Elnur Ibrahim Albashir, Abdulhamid Aidarous Alamir.