Iyad Katib¹, Mahmoud Ragab^2,*

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3749-3765, 2023, DOI:10.32604/csse.2023.036796

Abstract The concept of smart healthcare has seen a gradual increase with the expansion of information technology. Smart healthcare will use a new generation of information technologies, like artificial intelligence, the Internet of Things (IoT), cloud computing, and big data, to transform the conventional medical system in an all-around way, making healthcare highly effective, more personalized, and more convenient. This work designs a new Heap Based Optimization with Deep Quantum Neural Network (HBO-DQNN) model for decision-making in smart healthcare applications. The presented HBO-DQNN model majorly focuses on identifying and classifying healthcare data. In the presented HBO-DQNN model, three stages of operations… More >

Jiwon Jeon, Junho Kim, Mincheol Shin, Mucheol Kim^*

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3403-3421, 2023, DOI:10.32604/csse.2023.036658

Abstract The development of information technology allows the collaborative business process to be run across multiple enterprises in a larger market environment. However, while collaborative business expands the realm of businesses, it also causes various hazards in collaborative Interaction, such as data falsification, inconstancy, and misuse. To solve these issues, a blockchain-based collaborative business modeling approach was proposed and analyzed. However, the existing studies lack the blockchain risk problem-solving specification, and there is no verification technique to examine the process. Consequently, it is difficult to confirm the appropriateness of the approach. Thus, here, we propose and build a blockchain-based trust model… More >

Chaudhary Hassan Abbas Gondal^1,*, Muhammad Irfan², Sarmad Shafique³, Muhammad Salman Bashir⁴, Mansoor Ahmed¹, Osama M.Alshehri⁵, Hassan H. Almasoudi⁵, Samar M. Alqhtani⁶, Mohammed M. Jalal⁷, Malik A. Altayar⁷, Khalaf F. Alsharif⁸

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3541-3558, 2023, DOI:10.32604/csse.2023.036476

Abstract Leukemia is a kind of blood cancer that damages the cells in the blood and bone marrow of the human body. It produces cancerous blood cells that disturb the human’s immune system and significantly affect bone marrow’s production ability to effectively create different types of blood cells like red blood cells (RBCs) and white blood cells (WBC), and platelets. Leukemia can be diagnosed manually by taking a complete blood count test of the patient’s blood, from which medical professionals can investigate the signs of leukemia cells. Furthermore, two other methods, microscopic inspection of blood smears and bone marrow aspiration, are… More >

Abeera Ilyas^1,*, Saeed Mahfooz¹, Zahid Mehmood^2,3, Gauhar Ali⁴, Muhammad ElAffendi⁴

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3815-3829, 2023, DOI:10.32604/csse.2023.036316

Abstract Health monitoring systems are now required, particularly for essential patients, following the COVID-19 pandemic, which was followed by its variants and other epidemics of a similar nature. Effective procedures and strategies are required, though, to react promptly to the enormous volume of real-time data offered by monitoring equipment. Although fog-based designs for IoT health systems typically result in enhanced services, they also give rise to issues that need to be resolved. In this paper, we propose a two-way strategy to reduce network latency and use while increasing real-time data transmission of device gateways used for sensors by making educated judgments… More >

Baraa Wasfi Salim¹, Bzar Khidir Hussan², Zainab Salih Ageed³, Subhi R. M. Zeebaree^4,*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4593-4609, 2023, DOI:10.32604/cmc.2023.037514

Abstract Recently, human healthcare from body sensor data has gained considerable interest from a wide variety of human-computer communication and pattern analysis research owing to their real-time applications namely smart healthcare systems. Even though there are various forms of utilizing distributed sensors to monitor the behavior of people and vital signs, physical human action recognition (HAR) through body sensors gives useful information about the lifestyle and functionality of an individual. This article concentrates on the design of an Improved Transient Search Optimization with Machine Learning based Behavior Recognition (ITSOML-BR) technique using body sensor data. The presented ITSOML-BR technique collects data from… More >

Saeed Ali Alsareii¹, Mohsin Raza², Abdulrahman Manaa Alamri¹, Mansour Yousef AlAsmari¹, Muhammad Irfan³, Hasan Raza⁴, Muhammad Awais^2,*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3833-3848, 2023, DOI:10.32604/cmc.2023.035686

Abstract Obesity poses several challenges to healthcare and the well-being of individuals. It can be linked to several life-threatening diseases. Surgery is a viable option in some instances to reduce obesity-related risks and enable weight loss. State-of-the-art technologies have the potential for long-term benefits in post-surgery living. In this work, an Internet of Things (IoT) framework is proposed to effectively communicate the daily living data and exercise routine of surgery patients and patients with excessive weight. The proposed IoT framework aims to enable seamless communications from wearable sensors and body networks to the cloud to create an accurate profile of the… More >

Md. Moddassir Alam¹, Md Mottahir Alam², Muhammad Moinuddin^2,3, Mohammad Tauheed Ahmad⁴, Jabir Hakami⁵, Anis Ahmad Chaudhary⁶, Asif Irshad Khan⁷, Tauheed Khan Mohd^8,*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4553-4571, 2023, DOI:10.32604/cmc.2023.032118

Abstract Artificial Intelligence (AI) is finding increasing application in healthcare monitoring. Machine learning systems are utilized for monitoring patient health through the use of IoT sensor, which keep track of the physiological state by way of various health data. Thus, early detection of any disease or derangement can aid doctors in saving patients’ lives. However, there are some challenges associated with predicting health status using the common algorithms, such as time requirements, chances of errors, and improper classification. We propose an Artificial Krill Herd based on the Random Forest (AKHRF) technique for monitoring patients’ health and eliciting an optimal prescription based… More >

V. Gowri^1,*, V. Vijaya Chamundeeswari²

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3675-3690, 2023, DOI:10.32604/iasc.2023.035817

Abstract Decision forest is a well-renowned machine learning technique to address the detection and prediction problems related to clinical data. But, the traditional decision forest (DF) algorithms have lower classification accuracy and cannot handle high-dimensional feature space effectively. In this work, we propose a bootstrap decision forest using penalizing attributes (BFPA) algorithm to predict heart disease with higher accuracy. This work integrates a significance-based attribute selection (SAS) algorithm with the BFPA classifier to improve the performance of the diagnostic system in identifying cardiac illness. The proposed SAS algorithm is used to determine the correlation among attributes and to select the optimum… More >

Hosam Alhakami^1,*, Abdullah Baz², Mohammad Al-shareef³, Rajeev Kumar⁴, Alka Agrawal⁵, Raees Ahmad Khan⁵

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2773-2786, 2023, DOI:10.32604/iasc.2023.021560

Abstract Recent transformation of Saudi Arabian healthcare sector into a revenue producing one has signaled several advancements in healthcare in the country. Transforming healthcare management into Smart hospital systems is one of them. Secure hospital management systems which are breach-proof only can be termed as effective smart hospital systems. Given the perspective of Saudi Vision-2030, many practitioners are trying to achieve a cost-effective hospital management system by using smart ideas. In this row, the proposed framework posits the main objectives for creating smart hospital management systems that can only be acknowledged by managing the security of healthcare data and medical practices.… More >

Regina Lai-Tong Lee^1,2,*, Anson Chiu-Yan Tang³, Ho-Yu Cheng¹, Connie Yuen-Yu Chong¹, Wilson Wai-San Tam⁴, Wai-Tong Chien¹, Sally Wai-Chi Chan⁵

International Journal of Mental Health Promotion, Vol.25, No.3, pp. 327-342, 2023, DOI:10.32604/ijmhp.2022.026388

Abstract The present study aimed to examine work environment related factors and frontline primary healthcare professionals’ mental-emotional wellbeing during the COVID-19 pandemic in school communities of Hong Kong. A total of 61 (20%) school health nurses (frontline primary healthcare professionals) participated in a cross-sectional online survey from March to June 2020. Outcomes of mental-emotional health were measured using the Mental Health Continuum-Short Form (14-item scale with three subscales related to emotional, social and psychological wellbeing); the Perceived Stress Scale (10-item scale with two subscales related to perceived helplessness and lack of self-efficacy; and the Coping Orientation to Problems Experienced Inventory (Brief… More >