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 >

Nataliya Shakhovska¹, Nataliia Melnykova^1,*, Valentyna Chopiyak², Michal Gregus ml³

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3969-3984, 2022, DOI:10.32604/cmc.2022.019882

Abstract The paper reports three new ensembles of supervised learning predictors for managing medical insurance costs. The open dataset is used for data analysis methods development. The usage of artificial intelligence in the management of financial risks will facilitate economic wear time and money and protect patients’ health. Machine learning is associated with many expectations, but its quality is determined by choosing a good algorithm and the proper steps to plan, develop, and implement the model. The paper aims to develop three new ensembles for individual insurance costs prediction to provide high prediction accuracy. Pierson coefficient and Boruta algorithm are used… More >

Ahmed Ismail Ebada¹, Ibrahim Elhenawy², Chang-Won Jeong³, Yunyoung Nam^4,*, Hazem Elbakry¹, Samir Abdelrazek¹

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3511-3527, 2022, DOI:10.32604/cmc.2022.019458

Abstract Big data applications in healthcare have provided a variety of solutions to reduce costs, errors, and waste. This work aims to develop a real-time system based on big medical data processing in the cloud for the prediction of health issues. In the proposed scalable system, medical parameters are sent to Apache Spark to extract attributes from data and apply the proposed machine learning algorithm. In this way, healthcare risks can be predicted and sent as alerts and recommendations to users and healthcare providers. The proposed work also aims to provide an effective recommendation system by using streaming medical data, historical… More >

Jinsu Kim¹, Sungwook Ryu², Namje Park^1,3,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4169-4184, 2022, DOI:10.32604/cmc.2022.019277

Abstract A significant number of cloud storage environments are already implementing deduplication technology. Due to the nature of the cloud environment, a storage server capable of accommodating large-capacity storage is required. As storage capacity increases, additional storage solutions are required. By leveraging deduplication, you can fundamentally solve the cost problem. However, deduplication poses privacy concerns due to the structure itself. In this paper, we point out the privacy infringement problem and propose a new deduplication technique to solve it. In the proposed technique, since the user’s map structure and files are not stored on the server, the file uploader list cannot… More >

Azza Abdullah Alnssayan, Mohammad Mahdi Hassan^*, Suliman A. Alsuhibany

Computer Systems Science and Engineering, Vol.40, No.3, pp. 927-945, 2022, DOI:10.32604/csse.2022.016734

Abstract The digitalization of healthcare-related information service systems has become a trend across the world. However, several crucial services are still provided manually due to a lack of trust in digital solutions. One such service is keeping records of children’s vaccination, which still relies on a paper-based file system in most parts of the world. This approach causes serious data integrity problems. Recently, healthcare has become a potential application area of the blockchain, as it can preserve and protect highly sensitive private medical records while sharing these records in a decentralized manner without losing personal ownership. Therefore, we propose a new… More >

Mesfer Alrizq¹, Shauban Ali Solangi², Abdullah Alghamdi^1,*, Muhammad Ali Nizamani², Muhammad Ali Memon², Mohammed Hamdi¹

Computer Systems Science and Engineering, Vol.40, No.2, pp. 557-569, 2022, DOI:10.32604/csse.2022.018800

Abstract Recent advancements in the Internet of Things IoT and cloud computing have paved the way for mobile Healthcare (mHealthcare) services. A patient within the hospital is monitored by several devices. Moreover, upon leaving the hospital, the patient can be remotely monitored whether directly using body wearable sensors or using a smartphone equipped with sensors to monitor different user-health parameters. This raises potential challenges for intelligent monitoring of patient’s health. In this paper, an improved architecture for smart mHealthcare is proposed that is supported by HCI design principles. The HCI also provides the support for the User-Centric Design (UCD) for smart… More >

Taesik Lee¹, Dongsan Jun^1,*, Sang-hyo Park², Byung-Gyu Kim³, Jungil Yun⁴, Kugjin Yun⁴, Won-Sik Cheong⁴

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 2013-2029, 2022, DOI:10.32604/cmc.2022.019604

Abstract As video compression is one of the core technologies required to enable seamless medical data streaming in mobile healthcare applications, there is a need to develop powerful media codecs that can achieve minimum bitrates while maintaining high perceptual quality. Versatile Video Coding (VVC) is the latest video coding standard that can provide powerful coding performance with a similar visual quality compared to the previously developed method that is High Efficiency Video Coding (HEVC). In order to achieve this improved coding performance, VVC adopted various advanced coding tools, such as flexible Multi-type Tree (MTT) block structure which uses Binary Tree (BT)… More >

Adil Hussain Seh¹, Jehad F. Al-Amri², Ahmad F. Subahi³, Md Tarique Jamal Ansari¹, Rajeev Kumar^4,*, Mohammad Ubaidullah Bokhari⁵, Raees Ahmad Khan¹

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 469-489, 2022, DOI:10.32604/cmc.2022.019593

Abstract Transformation from conventional business management systems to smart digital systems is a recurrent trend in the current era. This has led to digital revolution, and in this context, the hardwired technologies in the software industry play a significant role However, from the beginning, software security remains a serious issue for all levels of stakeholders. Software vulnerabilities lead to intrusions that cause data breaches and result in disclosure of sensitive data, compromising the organizations’ reputation that translates into, financial losses as well. Most of the data breaches are financially motivated, especially in the healthcare sector. The cyber invaders continuously penetrate the… More >

R. Sujitha^*, B. Paramasivan

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1557-1572, 2022, DOI:10.32604/cmc.2022.019323

Abstract With the modernization of machine learning techniques in healthcare, different innovations including support vector machine (SVM) have predominantly played a major role in classifying lung cancer, predicting coronavirus disease 2019, and other diseases. In particular, our algorithm focuses on integrated datasets as compared with other existing works. In this study, parallel-based SVM (P-SVM) and multiclass-based multiple submodels (MMSM-SVM) were used to analyze the optimal classification of lung diseases. This analysis aimed to find the optimal classification of lung diseases with id and stages, such as key-value pairs in MapReduce combined with P-SVM and MMSVM for binary and multiclasses, respectively. For… More >

Ahed Abugabah^1,*, Louis Sanzogni², Luke Houghton², Ahmad Ali AlZubi³, Alaa Abuqabbeh⁴

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1335-1348, 2022, DOI:10.32604/cmc.2022.019097

Abstract Radio frequency identification (RFID), also known as electronic label technology, is a non-contact automated identification technology that recognizes the target object and extracts relevant data and critical characteristics using radio frequency signals. Medical equipment information management is an important part of the construction of a modern hospital, as it is linked to the degree of diagnosis and care, as well as the hospital’s benefits and growth. The aim of this study is to create an integrated view of a theoretical framework to identify factors that influence RFID adoption in healthcare, as well as to conduct an empirical review of the… More >