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  • Open Access


    Telepresence Robots and Controlling Techniques in Healthcare System

    Fawad Naseer1,*, Muhammad Nasir Khan1, Zubair Nawaz2, Qasim Awais3

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6623-6639, 2023, DOI:10.32604/cmc.2023.035218

    Abstract In this era of post-COVID-19, humans are psychologically restricted to interact less with other humans. According to the world health organization (WHO), there are many scenarios where human interactions cause severe multiplication of viruses from human to human and spread worldwide. Most healthcare systems shifted to isolation during the pandemic and a very restricted work environment. Investigations were done to overcome the remedy, and the researcher developed different techniques and recommended solutions. Telepresence robot was the solution achieved by all industries to continue their operations but with almost zero physical interaction with other humans. It… More >

  • Open Access


    Dm-Health App: Diabetes Diagnosis Using Machine Learning with Smartphone

    Elias Hossain1, Mohammed Alshehri2, Sultan Almakdi2,*, Hanan Halawani2, Md. Mizanur Rahman3, Wahidur Rahman4, Sabila Al Jannat5, Nadim Kaysar6, Shishir Mia4

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1713-1746, 2022, DOI:10.32604/cmc.2022.024822

    Abstract Diabetes Mellitus is one of the most severe diseases, and many studies have been conducted to anticipate diabetes. This research aimed to develop an intelligent mobile application based on machine learning to determine the diabetic, pre-diabetic, or non-diabetic without the assistance of any physician or medical tests. This study's methodology was classified into two the Diabetes Prediction Approach and the Proposed System Architecture Design. The Diabetes Prediction Approach uses a novel approach, Light Gradient Boosting Machine (LightGBM), to ensure a faster diagnosis. The Proposed System Architecture Design has been combined into seven modules; the Answering… More >

  • Open Access


    Traffic Priority-Aware Medical Data Dissemination Scheme for IoT Based WBASN Healthcare Applications

    Muhammad Anwar1, Farhan Masud2, Rizwan Aslam Butt3, Sevia Mahdaliza Idrus4,*, Mohammad Nazir Ahmad5, Mohd Yazid Bajuri6

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4443-4456, 2022, DOI:10.32604/cmc.2022.022826

    Abstract Wireless Body Area Sensor Network (WBASN) is an automated system for remote health monitoring of patients. WBASN under umbrella of Internet of Things (IoT) is comprised of small Biomedical Sensor Nodes (BSNs) that can communicate with each other without human involvement. These BSNs can be placed on human body or inside the skin of the patients to regularly monitor their vital signs. The BSNs generate critical data as it is related to patient's health. The data traffic can be classified as Sensitive Data (SD) and Non-sensitive Data (ND) packets based on the value of vital… More >

  • Open Access


    Deep Neural Artificial Intelligence for IoT Based Tele Health Data Analytics

    Nithya Rekha Sivakumar1,*, Ahmed Zohair Ibrahim2

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4467-4483, 2022, DOI:10.32604/cmc.2022.019041


    Tele health utilizes information and communication mechanisms to convey medical information for providing clinical and educational assistances. It makes an effort to get the better of issues of health service delivery involving time factor, space and laborious terrains, validating cost-efficiency and finer ingress in both developed and developing countries. Tele health has been categorized into either real-time electronic communication, or store-and-forward communication. In recent years, a third-class has been perceived as remote healthcare monitoring or tele health, presuming data obtained via Internet of Things (IOT). Although, tele health data analytics and machine learning have been researched

    More >

  • Open Access


    Utilization of HEVC ChaCha20-Based Selective Encryption for Secure Telehealth Video Conferencing

    Osama S. Faragallah1,*, Ahmed I. Sallam2, Hala S. El-sayed3

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 831-845, 2022, DOI:10.32604/cmc.2022.019151

    Abstract Coronavirus (COVID-19) is a contagious disease that causes exceptional effect on healthcare organizations worldwide with dangerous impact on medical services within the hospitals. Because of the fast spread of COVID-19, the healthcare facilities could be a big source of disease infection. So, healthcare video consultations should be used to decrease face-to-face communication between clinician and patients. Healthcare video consultations may be beneficial for some COVID-19 conditions and reduce the need for face-to-face contact with a potentially positive patient without symptoms. These conditions are like top clinicians who provide remote consultations to develop treatment methodology and… More >

  • Open Access


    Deep Learning Applications for COVID-19 Analysis: A State-of-the-Art Survey

    Wenqian Li1, Xing Deng1,2,*, Haijian Shao1, Xia Wang3

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 65-98, 2021, DOI:10.32604/cmes.2021.016981

    Abstract The COVID-19 has resulted in catastrophic situation and the deaths of millions of people all over the world. In this paper, the predictions of epidemiological propagation models, such as SIR and SEIR, are introduced to analyze the earlier COVID-19 propagation. The deep learning methods combined with transfer learning are familiar with classification-detection approaches based on chest X-ray and CT images are presented in detail. Besides, deep learning approaches have also been applied to lung ultrasound (LUS), which has been shown to be more sensitive than chest X-ray and CT images in detecting COVID-19. In the… More > Graphic Abstract

    Deep Learning Applications for COVID-19 Analysis: A <i>State-of-the-Art</i> Survey

  • Open Access


    HealthyBlockchain for Global Patients

    Shada A. Alsalamah1,2,3,*, Hessah A. Alsalamah1,4, Thamer Nouh5, Sara A. Alsalamah6

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2431-2449, 2021, DOI:10.32604/cmc.2021.016618

    Abstract An emerging healthcare delivery model is enabling a new era of clinical care based on well-informed decision-making processes. Current healthcare information systems (HISs) fall short of adopting this model due to a conflict between information security needed to implement the new model and those already enforced locally to support traditional care models. Meanwhile, in recent times, the healthcare sector has shown a substantial interest in the potential of using blockchain technology for providing quality care to patients. No blockchain solution proposed so far has fully addressed emerging cross-organization information-sharing needs in healthcare. In this paper, More >

  • Open Access


    Suitability of VVC and HEVC for Video Telehealth Systems

    Muhammad Arslan Usman1,4,*, Muhammad Rehan Usman2, Rizwan Ali Naqvi3, Bernie Mcphilips4, Christopher Romeika4, Daniel Cunliffe4, Christos Politis1, Nada Philip1

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 529-547, 2021, DOI:10.32604/cmc.2021.014614

    Abstract Video compression in medical video streaming is one of the key technologies associated with mobile healthcare. Seamless delivery of medical video streams over a resource constrained network emphasizes the need of a video codec that requires minimum bitrates and maintains high perceptual quality. This paper presents a comparative study between High Efficiency Video Coding (HEVC) and its potential successor Versatile Video Coding (VVC) in the context of healthcare. A large-scale subjective experiment comprising of twenty-four non-expert participants is presented for eight different test conditions in Full High Definition (FHD) videos. The presented analysis highlights the… More >

  • Open Access


    FogMed: A Fog-Based Framework for Disease Prognosis Based Medical Sensor Data Streams

    Le Sun1,*, Qiandi Yu1, Dandan Peng1, Sudha Subramani2, Xuyang Wang1

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 603-619, 2021, DOI:10.32604/cmc.2020.012515

    Abstract Recently, an increasing number of works start investigating the combination of fog computing and electronic health (ehealth) applications. However, there are still numerous unresolved issues worth to be explored. For instance, there is a lack of investigation on the disease prediction in fog environment and only limited studies show, how the Quality of Service (QoS) levels of fog services and the data stream mining techniques influence each other to improve the disease prediction performance (e.g., accuracy and time efficiency). To address these issues, we propose a fog-based framework for disease prediction based on Medical sensor More >

  • Open Access


    A Mobile Cloud-Based eHealth Scheme

    Yihe Liu1, Aaqif Afzaal Abbasi2, Atefeh Aghaei3, Almas Abbasi4, Amir Mosavi5, 6, 7, Shahaboddin Shamshirband8, 9, *, Mohammed A. A. Al-qaness10

    CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 31-39, 2020, DOI:10.32604/cmc.2020.07708

    Abstract Mobile cloud computing is an emerging field that is gaining popularity across borders at a rapid pace. Similarly, the field of health informatics is also considered as an extremely important field. This work observes the collaboration between these two fields to solve the traditional problem of extracting Electrocardiogram signals from trace reports and then performing analysis. The developed system has two front ends, the first dedicated for the user to perform the photographing of the trace report. Once the photographing is complete, mobile computing is used to extract the signal. Once the signal is extracted, More >

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