Mohamed Esmail Karar^1,2,*, Omar Reyad^1,3, Hazem Ibrahim Shehata^1,4

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2377-2389, 2023, DOI:10.32604/csse.2023.032931

Abstract This article introduces a new medical internet of things (IoT) framework for intelligent fall detection system of senior people based on our proposed deep forest model. The cascade multi-layer structure of deep forest classifier allows to generate new features at each level with minimal hyperparameters compared to deep neural networks. Moreover, the optimal number of the deep forest layers is automatically estimated based on the early stopping criteria of validation accuracy value at each generated layer. The suggested forest classifier was successfully tested and evaluated using a public SmartFall dataset, which is acquired from three-axis accelerometer in a smartwatch. It… More >

Hong’an Li¹, Min Zhang^1,*, Dufeng Chen², Jing Zhang¹, Meng Yang³, Zhanli Li¹

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 779-794, 2023, DOI:10.32604/cmes.2022.022369

Abstract Computer-aided diagnosis based on image color rendering promotes medical image analysis and doctor-patient communication by highlighting important information of medical diagnosis. To overcome the limitations of the color rendering method based on deep learning, such as poor model stability, poor rendering quality, fuzzy boundaries and crossed color boundaries, we propose a novel hinge-cross-entropy generative adversarial network (HCEGAN). The self-attention mechanism was added and improved to focus on the important information of the image. And the hinge-cross-entropy loss function was used to stabilize the training process of GAN models. In this study, we implement the HCEGAN model for image color rendering… More > Graphic Abstract

G. Ignisha Rajathi¹, R. Ramesh Kumar², D. Ravikumar³, T. Joel⁴, Seifedine Kadry^4,5, Chang-Won Jeong⁶, Yunyoung Nam^7,*

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1793-1806, 2023, DOI:10.32604/csse.2023.024674

Abstract Recently, Internet of Medical Things (IoMT) has gained considerable attention to provide improved healthcare services to patients. Since earlier diagnosis of brain tumor (BT) using medical imaging becomes an essential task, automated IoMT and cloud enabled BT diagnosis model can be devised using recent deep learning models. With this motivation, this paper introduces a novel IoMT and cloud enabled BT diagnosis model, named IoMTC-HDBT. The IoMTC-HDBT model comprises the data acquisition process by the use of IoMT devices which captures the magnetic resonance imaging (MRI) brain images and transmit them to the cloud server. Besides, adaptive window filtering (AWF) based… More >

K. S. Riya¹, R. Surendran^2,*, Carlos Andrés Tavera Romero³, M. Sadish Sendil⁴

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 507-520, 2023, DOI:10.32604/iasc.2023.027779

Abstract Internet of Medical Things (IoMT) enabled e-healthcare has the potential to greately improve conventional healthcare services significantly. However, security and privacy become major issues of IoMT because of the restricted processing abilities, storage, and energy constraints of the sensors. Therefore, it leads to infeasibility of developing traditional cryptographic solutions to the IoMT sensors. In order to ensure security on sensitive medical data, effective encryption and authentication techniques need to be designed to assure security of the patients and healthcare service providers. In this view, this study designs an effective metaheuristic optimization based encryption with user authentication (EMOE-UA) technique for IoMT… More >

Sultan Ahmad¹, Shakir Khan², Mohamed Fahad AlAjmi³, Ashit Kumar Dutta⁴, L. Minh Dang⁵, Gyanendra Prasad Joshi⁶, Hyeonjoon Moon^6,*

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 965-979, 2022, DOI:10.32604/cmc.2022.025760

Abstract In recent times, Internet of Medical Things (IoMT) gained much attention in medical services and healthcare management domain. Since healthcare sector generates massive volumes of data like personal details, historical medical data, hospitalization records, and discharging records, IoMT devices too evolved with potentials to handle such high quantities of data. Privacy and security of the data, gathered by IoMT gadgets, are major issues while transmitting or saving it in cloud. The advancements made in Artificial Intelligence (AI) and encryption techniques find a way to handle massive quantities of medical data and achieve security. In this view, the current study presents… More >

Romany F. Mansour^1,*, Maha M. Althobaiti²

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3945-3959, 2022, DOI:10.32604/cmc.2022.026515

Abstract Recently, the Internet of Medical Things (IoMT) has become a research hotspot due to its various applicability in medical field. However, the data analysis and management in IoMT remain challenging owing to the existence of a massive number of devices linked to the server environment, generating a massive quantity of healthcare data. In such cases, cognitive computing can be employed that uses many intelligent technologies–machine learning (ML), deep learning (DL), artificial intelligence (AI), natural language processing (NLP) and others–to comprehend data expansively. Furthermore, breast cancer (BC) has been found to be a major cause of mortality among ladies globally. Earlier… More >

Anwer Mustafa Hilal^1,*, Siwar Ben Haj Hassine², Souad Larabi-Marie-Sainte³, Nadhem Nemri², Mohamed K. Nour⁴, Abdelwahed Motwakel¹, Abu Sarwar Zamani¹, Mesfer Al Duhayyim⁵

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 713-726, 2022, DOI:10.32604/cmc.2022.024501

Abstract The development in Information and Communication Technology has led to the evolution of new computing and communication environment. Technological revolution with Internet of Things (IoTs) has developed various applications in almost all domains from health care, education to entertainment with sensors and smart devices. One of the subsets of IoT is Internet of Medical things (IoMT) which connects medical devices, hardware and software applications through internet. IoMT enables secure wireless communication over the Internet to allow efficient analysis of medical data. With these smart advancements and exploitation of smart IoT devices in health care technology there increases threat and malware… More >

Hameed AlQaheri^1,*, Manash Sarkar², Saptarshi Gupta³, Bhavya Gaur⁴

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 497-517, 2022, DOI:10.32604/cmc.2022.022735

Abstract The most common alarming and dangerous disease in the world today is the coronavirus disease 2019 (COVID-19). The coronavirus is perceived as a group of coronaviruses which causes mild to severe respiratory diseases among human beings. The infection is spread by aerosols emitted from infected individuals during talking, sneezing, and coughing. Furthermore, infection can occur by touching a contaminated surface followed by transfer of the viral load to the face. Transmission may occur through aerosols that stay suspended in the air for extended periods of time in enclosed spaces. To stop the spread of the pandemic, it is crucial to… More >

Chaoyang Li^1,*, Yalan Wang², Gang Xu³, Xiubo Chen⁴, Xiangjun Xin¹, Jian Li⁴

Journal of Cyber Security, Vol.3, No.4, pp. 207-216, 2021, DOI:10.32604/jcs.2021.026926

Abstract Along with the increase of wearable medical device, the privacy leakage problem in the process of transmission between these edge medical devices. The blockchain-enabled Internet of Medical Things (BIoMT) has been developed to reform traditional centralized medical system in recent years. This paper first introduces a data anonymous authentication model to protect user privacy and medical data in BIoMT. Then, a proxy group signature (PGS) scheme has been proposed based on lattice assumption. This scheme can well satisfy the anonymous authentication demand for the proposed model, and provide anti-quantum attack security for BIoMT in the future general quantum computer age.… More >

J. P. Shri Tharanyaa^1,*, D. Sharmila², R. Saravana Kumar³

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2667-2681, 2022, DOI:10.32604/cmc.2022.019889

Abstract With the emergence of the Internet of things (IoT), embedded systems have now changed its dimensionality and it is applied in various domains such as healthcare, home automation and mainly Industry 4.0. These Embedded IoT devices are mostly battery-driven. It has been analyzed that usage of Dynamic Random-Access Memory (DRAM) centered core memory is considered the most significant source of high energy utility in Embedded IoT devices. For achieving the low power consumption in these devices, Non-volatile memory (NVM) devices such as Parameter Random Access Memory (PRAM) and Spin-Transfer Torque Magnetic Random-Access Memory (STT-RAM) are becoming popular among main memory… More >