Anika Tahsin Meem¹, Mohammad Monirujjaman Khan^1,*, Mehedi Masud², Sultan Aljahdali²

Computer Systems Science and Engineering, Vol.41, No.3, pp. 1223-1240, 2022, DOI:10.32604/csse.2022.021563

Abstract The COVID-19 pandemic has caused trouble in people’s daily lives and ruined several economies around the world, killing millions of people thus far. It is essential to screen the affected patients in a timely and cost-effective manner in order to fight this disease. This paper presents the prediction of COVID-19 with Chest X-Ray images, and the implementation of an image processing system operated using deep learning and neural networks. In this paper, a Deep Learning, Machine Learning, and Convolutional Neural Network-based approach for predicting Covid-19 positive and normal patients using Chest X-Ray pictures is proposed. In this study, machine learning… More >

P. Prabu¹, K. Venkatachalam², Ala Saleh Alluhaidan^3,*, Radwa Marzouk⁴, Myriam Hadjouni⁵, Sahar A. El_Rahman^5,6

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1133-1152, 2022, DOI:10.32604/cmc.2022.020919

Abstract COVID’19 has caused the entire universe to be in existential health crisis by spreading globally in the year 2020. The lungs infection is detected in Computed Tomography (CT) images which provide the best way to increase the existing healthcare schemes in preventing the deadly virus. Nevertheless, separating the infected areas in CT images faces various issues such as low-intensity difference among normal and infectious tissue and high changes in the characteristics of the infection. To resolve these issues, a new inf-Net (Lung Infection Segmentation Deep Network) is designed for detecting the affected areas from the CT images automatically. For the… More >

M. A. El Safty^1,*, S. A. Alblowi², Yahya Almalki³, M. El Sayed⁴

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 483-498, 2022, DOI:10.32604/iasc.2022.021581

Abstract Real-world applications now deal with a massive amount of data, and information about the world is inaccurate, incomplete, or uncertain. Therefore, we present in our paper a proposed model for solving problems. This model is based on the class of locally generalized closed sets, namely, locally simply* alpha generalized closed* sets and locally simply* alpha generalized closed** sets (briefly, -sets and -sets), based on simply* alpha open set. We also introduce various concepts of their properties and their relationship with other types, and we are studying several of their properties. Finally, we apply the concept of the simply* alpha open… More >

Abdulwahab Ali Almazroi¹, Raja Sher Afgun Usmani^2,*

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 389-400, 2022, DOI:10.32604/iasc.2022.020588

Abstract COVID-19 pandemic has affected more than 144 million people and spread to over 200 countries. The prediction of COVID-19 behaviour and trend is crucial to prevent its spreading. Kingdom of Saudi Arabia (KSA) is Asia’s fifth largest country, and it hosts the two holiest cities of the Islamic world. KSA hosts millions of pilgrims every year, and it is of great importance to predict the COVID-19 spread to organize these religious activities and bring life to normality in KSA. This study proposes four tree-based ensemble methods to predict the COVID-19 daily new cases in KSA. Tree-based ensemble methods are suggested… More >

Tallat Jabeen^1,2, Ishrat Jabeen¹, Humaira Ashraf², Nz Jhanjhi^3,*, Mamoona Humayun⁴, Mehedi Masud⁵, Sultan Aljahdali⁵

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2365-2380, 2022, DOI:10.32604/cmc.2022.020016

Abstract COVID-19 is a novel coronavirus disease that has been declared as a global pandemic in 2019. It affects the whole world through person-to-person communication. This virus spreads by the droplets of coughs and sneezing, which are quickly falling over the surface. Therefore, anyone can get easily affected by breathing in the vicinity of the COVID-19 patient. Currently, vaccine for the disease is under clinical investigation in different pharmaceutical companies. Until now, multiple medical companies have delivered health monitoring kits. However, a wireless body area network (WBAN) is a healthcare system that consists of nano sensors used to detect the real-time… More >

Mamoona Humayun^1,*, Ahmed Alsayat²

Computer Systems Science and Engineering, Vol.40, No.3, pp. 947-961, 2022, DOI:10.32604/csse.2022.019288

Abstract The recent global outbreak of COVID-19 damaged the world health systems, human health, economy, and daily life badly. None of the countries was ready to face this emerging health challenge. Health professionals were not able to predict its rise and next move, as well as the future curve and impact on lives in case of a similar pandemic situation happened. This created huge chaos globally, for longer and the world is still struggling to come up with any suitable solution. Here the better use of advanced technologies, such as artificial intelligence and deep learning, may aid healthcare practitioners in making… More >

Rehan Ullah Khan^*, Waleed Albattah, Suliman Aladhadh, Shabana Habib

Computer Systems Science and Engineering, Vol.40, No.2, pp. 765-777, 2022, DOI:10.32604/csse.2022.019757

Abstract Coronavirus disease, which resulted from the SARS-CoV-2 virus, has spread worldwide since early 2020 and has been declared a pandemic by the World Health Organization (WHO). Coronavirus disease is also termed COVID-19. It affects the human respiratory system and thus can be traced and tracked from the Chest X-Ray images. Therefore, Chest X-Ray alone may play a vital role in identifying COVID-19 cases. In this paper, we propose a Machine Learning (ML) approach that utilizes the X-Ray images to classify the healthy and affected patients based on the patterns found in these images. The article also explores traditional, and Deep… More >

Mohammed Baz¹, Sabita Khatri², Abdullah Baz³, Hosam Alhakami⁴, Alka Agrawal², Raees Ahmad Khan^2,*

Computer Systems Science and Engineering, Vol.40, No.2, pp. 691-702, 2022, DOI:10.32604/csse.2022.019079

Abstract The rapid emergence of novel virus named SARS-CoV2 and unchecked dissemination of this virus around the world ever since its outbreak in 2020, provide critical research criteria to assess the vulnerabilities of our current health system. The paper addresses our preparedness for the management of such acute health emergencies and the need to enhance awareness, about public health and healthcare mechanisms. In view of this unprecedented health crisis, distributed ledger and AI technology can be seen as one of the promising alternatives for fighting against such epidemics at the early stages, and with the higher efficacy. At the implementation level,… More >

Indrajeet Kumar¹, Sultan S. Alshamrani², Abhishek Kumar³, Jyoti Rawat⁴, Kamred Udham Singh¹, Mamoon Rashid^5,*, Ahmed Saeed AlGhamdi⁶

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 451-468, 2022, DOI:10.32604/cmc.2022.019443

Abstract Early diagnosis of a pandemic disease like COVID-19 can help deal with a dire situation and help radiologists and other experts manage human resources more effectively. In a recent pandemic, laboratories perform diagnostics manually, which requires a lot of time and expertise of the laboratorial technicians to yield accurate results. Moreover, the cost of kits is high, and well-equipped labs are needed to perform this test. Therefore, other means of diagnosis is highly desirable. Radiography is one of the existing methods that finds its use in the diagnosis of COVID-19. The radiography observes change in Computed Tomography (CT) chest images… More >

M. A. El Safty^1,*, Samirah Al Zahrani¹, M. K. El-Bably², M. El Sayed³

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 267-285, 2022, DOI:10.32604/cmc.2022.019345

Abstract In this paper, we present a proposed method for generating a soft rough approximation as a modification and generalization of Zhaowen et al. approach. Comparisons were obtained between our approach and the previous study and also. Eventually, an application on Coronavirus (COVID-19) has been presented, illustrated using our proposed concept, and some influencing results for symptoms of Coronavirus patients have been deduced. Moreover, following these concepts, we construct an algorithm and apply it to a decision-making problem to demonstrate the applicability of our proposed approach. Finally, a proposed approach that competes with others has been obtained, as well as realistic… More >