B. Karthikeyan^1,*, K. Nithya², Ahmed Alkhayyat³, Yousif Kerrar Yousif⁴

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2299-2313, 2023, DOI:10.32604/iasc.2023.032585

Abstract In today’s digital era, e-healthcare systems exploit digital technologies and telecommunication devices such as mobile devices, computers and the internet to provide high-quality healthcare services. E-healthcare decision support systems have been developed to optimize the healthcare services and enhance a patient’s health. These systems enable rapid access to the specialized healthcare services via reliable information, retrieved from the cases or the patient histories. This phenomenon reduces the time taken by the patients to physically visit the healthcare institutions. In the current research work, a new Shuffled Frog Leap Optimizer with Deep Learning-based Decision Support System (SFLODL-DSS) is designed for the… More >

Hanan Abdullah Mengash¹, Lubna A. Alharbi², Saud S. Alotaibi³, Sarab AlMuhaideb⁴, Nadhem Nemri⁵, Mrim M. Alnfiai⁶, Radwa Marzouk¹, Ahmed S. Salama⁷, Mesfer Al Duhayyim^8,*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4483-4500, 2023, DOI:10.32604/cmc.2023.032588

Abstract In recent times, cities are getting smart and can be managed effectively through diverse architectures and services. Smart cities have the ability to support smart medical systems that can infiltrate distinct events (i.e., smart hospitals, smart homes, and community health centres) and scenarios (e.g., rehabilitation, abnormal behavior monitoring, clinical decision-making, disease prevention and diagnosis postmarking surveillance and prescription recommendation). The integration of Artificial Intelligence (AI) with recent technologies, for instance medical screening gadgets, are significant enough to deliver maximum performance and improved management services to handle chronic diseases. With latest developments in digital data collection, AI techniques can be employed… More >

Punit Gupta¹, Sanjit Bhagat², Dinesh Kumar Saini^1,*, Ashish Kumar², Mohammad Alahmadi³, Prakash Chandra Sharma¹

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5659-5676, 2022, DOI:10.32604/cmc.2022.023056

Abstract In the next generation of computing environment e-health care services depend on cloud services. The Cloud computing environment provides a real-time computing environment for e-health care applications. But these services generate a huge number of computational tasks, real-time computing and comes with a deadline, so conventional cloud optimization models cannot fulfil the task in the least time and within the deadline. To overcome this issue many resource optimization meta-heuristic models are been proposed but these models cannot find a global best solution to complete the task in the least time and manage utilization with the least simulation time. In order… More >

Muhammad Sajjad¹, Tauqeer Safdar Malik¹, Shahzada Khurram², Akber Abid Gardezi³, Fawaz Alassery⁴, Habib Hamam⁵, Omar Cheikhrouhou⁶, Muhammad Shafiq^7,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2739-2753, 2022, DOI:10.32604/cmc.2022.022706

Abstract Many patients have begun to use mobile applications to handle different health needs because they can better access high-speed Internet and smartphones. These devices and mobile applications are now increasingly used and integrated through the medical Internet of Things (mIoT). mIoT is an important part of the digital transformation of healthcare, because it can introduce new business models and allow efficiency improvements, cost control and improve patient experience. In the mIoT system, when migrating from traditional medical services to electronic medical services, patient protection and privacy are the priorities of each stakeholder. Therefore, it is recommended to use different user… More >

C. Rajinikanth¹, P. Selvaraj², Mohamed Yacin Sikkandar³, T. Jayasankar⁴, Seifedine Kadry⁵, Yunyoung Nam^6,*

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2013-2029, 2021, DOI:10.32604/cmc.2021.018719

Abstract Internet of Things (IoT) has become a major technological development which offers smart infrastructure for the cloud-edge services by the interconnection of physical devices and virtual things among mobile applications and embedded devices. The e-healthcare application solely depends on the IoT and cloud computing environment, has provided several characteristics and applications. Prior research works reported that the energy consumption for transmission process is significantly higher compared to sensing and processing, which led to quick exhaustion of energy. In this view, this paper introduces a new energy efficient cluster enabled clinical decision support system (EEC-CDSS) for embedded IoT environment. The presented… More >