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  • Open Access

    ARTICLE

    A Hybrid Deep Learning Model for COVID-19 Prediction and Current Status of Clinical Trials Worldwide

    Shwet Ketu*, Pramod Kumar Mishra

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1896-1919, 2021, DOI:10.32604/cmc.2020.012423

    Abstract Infections or virus-based diseases are a significant threat to human societies and could affect the whole world within a very short time-span. Corona Virus Disease-2019 (COVID-19), also known as novel coronavirus or SARS-CoV-2 (Severe Acute Respiratory Syndrome-Coronavirus-2), is a respiratory based touch contiguous disease. The catastrophic situation resulting from the COVID-19 pandemic posed a serious threat to societies globally. The whole world is making tremendous efforts to combat this life-threatening disease. For taking remedial action and planning preventive measures on time, there is an urgent need for efficient prediction models to confront the COVID-19 outbreak. A deep learning-based ARIMA-LSTM hybrid… More >

  • Open Access

    ARTICLE

    Deep Learning Based Intelligent and Sustainable Smart Healthcare Application in Cloud-Centric IoT

    K. V. Praveen1, P. M. Joe Prathap2, S. Dhanasekaran3, I. S. Hephzi Punithavathi4, P. Duraipandy5, Irina V. Pustokhina6, Denis A. Pustokhin7,*

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1987-2003, 2021, DOI:10.32604/cmc.2020.012398

    Abstract Recent developments in information technology can be attributed to the development of smart cities which act as a key enabler for next-generation intelligent systems to improve security, reliability, and efficiency. The healthcare sector becomes advantageous and offers different ways to manage patient information in order to improve healthcare service quality. The futuristic sustainable computing solutions in e-healthcare applications depend upon Internet of Things (IoT) in cloud computing environment. The energy consumed during data communication from IoT devices to cloud server is significantly high and it needs to be reduced with the help of clustering techniques. The current research article presents… More >

  • Open Access

    ARTICLE

    Frequencies Rotation at High Sound Pressure Levels Toward Low Frequencies

    Hadi Negahdari1, Sirus Javadpour2,*, Faramarz Moattar3

    Sound & Vibration, Vol.54, No.4, pp. 237-246, 2020, DOI:10.32604/sv.2020.011086

    Abstract Today, analyzing of sound pressure level and frequency is considered as an important index in human society. Sound experts believe that analyzing of these parameters can help us to better understanding of work environments. Sound measurements and frequency analysis did to fix the harmful frequency in all sections in Shiraz gas power plant with sound analyzer model BSWA 308. The sound pressure levels (LP) and the one and one-third octave band were continuously measured in A and C weighting networks and slow mode for time response. Excel 2013 and Minitab 18.1 software used for statistical calculations. Results analyzed by Minitab… More >

  • Open Access

    ARTICLE

    Health-Related Quality of Life, Emotional and Behavioral Problems in Children and Adolescents with Ebstein Anomaly

    Lianne M. Geerdink1,2,*, Malindi van der Mheen3,4, Gideon J. du Marchie Sarvaas5, Irene M. Kuipers6, Stefan Frerich7, Henriëtte ter Heide2, Willem A. Helbing8, Zina Feijzic1, Christian Schroer9, Chris L. de Korte10, Livia Kapusta1,11, Chris M. Verhaak12, Elisabeth M. W. J. Utens3,4

    Congenital Heart Disease, Vol.15, No.6, pp. 457-472, 2020, DOI:10.32604/CHD.2020.012994

    Abstract Background: Due to the improved survival rates of children and adolescents with congenital heart disease (CHD), more attention is now being directed towards their health-related quality of life (HRQoL), emotional and behavioral problems. Ebstein anomaly (EA) is a rare CHD with a broad clinical spectrum. The aim of the current study is to evaluate self- and proxy-reported HRQoL and emotional and behavioral problems in children and adolescents with EA. Methods: In this cross-sectional, multicenter study, we included EA patients (aged 8–17 years), who underwent routine clinical assessments in Dutch university hospitals between May 2017 and March 2019. The Generic Pediatric… More >

  • Open Access

    ARTICLE

    Long-Term Healthcare Utilization, Medical Cost, and Societal Cost in Adult Congenital Heart Disease

    Ruben Willems1,*, Fouke Ombelet2, Eva Goossens2,3,4, Katya De Groote5, Werner Budts6,7, Stéphane Moniotte8, Michèle de Hosson9, Liesbet Van Bulck2,4, Arianne Marelli10, Philip Moons2,11,12, Julie De Backer4,9,#, Lieven Annemans1,#

    Congenital Heart Disease, Vol.15, No.6, pp. 399-429, 2020, DOI:10.32604/CHD.2020.011709

    Abstract Objective: Cost-of-illness studies in Adult Congenital Heart Disease (ACHD) have mainly been limited to hospitalizations. This is the first paper to provide a comprehensive overview from a societal perspective including inpatient and outpatient medical costs, and absenteeism- and unemployment-related societal costs. Methods: A retrospective longitudinal (2006–2015) database analysis was performed in Belgium combining administrative and clinical databases (n = 10,572). Trends in resource use and costs per patient year were standardized to assess the impact of changes in the patient population composition. Generalized Linear Mixed Models assessed the impact of age, sex, lesion complexity, and time. Costs were converted to… More >

  • Open Access

    ARTICLE

    Artificial Intelligence-Based Semantic Segmentation of Ocular Regions for Biometrics and Healthcare Applications

    Rizwan Ali Naqvi1, Dildar Hussain2, Woong-Kee Loh3,*

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 715-732, 2021, DOI:10.32604/cmc.2020.013249

    Abstract Multiple ocular region segmentation plays an important role in different applications such as biometrics, liveness detection, healthcare, and gaze estimation. Typically, segmentation techniques focus on a single region of the eye at a time. Despite the number of obvious advantages, very limited research has focused on multiple regions of the eye. Similarly, accurate segmentation of multiple eye regions is necessary in challenging scenarios involving blur, ghost effects low resolution, off-angles, and unusual glints. Currently, the available segmentation methods cannot address these constraints. In this paper, to address the accurate segmentation of multiple eye regions in unconstrainted scenarios, a lightweight outer… More >

  • Open Access

    ARTICLE

    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 data streams, named FogMed. This… More >

  • Open Access

    ARTICLE

    Smart Healthcare Using Data-Driven Prediction of Immunization Defaulters in Expanded Program on Immunization (EPI)

    Sadaf Qazi1, Muhammad Usman1, Azhar Mahmood1, Aaqif Afzaal Abbasi2, Muhammad Attique3, Yunyoung Nam4,*

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 589-602, 2021, DOI:10.32604/cmc.2020.012507

    Abstract Immunization is a noteworthy and proven tool for eliminating lifethreating infectious diseases, child mortality and morbidity. Expanded Program on Immunization (EPI) is a nation-wide program in Pakistan to implement immunization activities, however the coverage is quite low despite the accessibility of free vaccination. This study proposes a defaulter prediction model for accurate identification of defaulters. Our proposed framework classifies defaulters at five different stages: defaulter, partially high, partially medium, partially low, and unvaccinated to reinforce targeted interventions by accurately predicting children at high risk of defaulting from the immunization schedule. Different machine learning algorithms are applied on Pakistan Demographic and… More >

  • Open Access

    ARTICLE

    Intelligent Tunicate Swarm-Optimization-Algorithm-Based Lightweight Security Mechanism in Internet of Health Things

    Gia Nhu Nguyen1,2, Nin Ho Le Viet1,2, Gyanendra Prasad Joshi3, Bhanu Shrestha4,*

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 551-562, 2021, DOI:10.32604/cmc.2020.012441

    Abstract Fog computing in the Internet of Health Things (IoHT) is promising owing to the increasing need for energy- and latency-optimized health sector provisioning. Additionally, clinical data (particularly, medical image data) are a delicate, highly protected resource that should be utilized in an effective and responsible manner to fulfil consumer needs. Herein, we propose an energy-effi- cient fog-based IoHT with a tunicate swarm-optimization-(TSO)-based lightweight Simon cipher to enhance the energy efficiency at the fog layer and the security of data stored at the cloud server. The proposed Simon cipher uses the TSO algorithm to select the optimal keys that will minimize… More >

  • Open Access

    ARTICLE

    A Smart Wellness Service Platform and Its Practical Implementation

    Umar Farooq1, Intae Ryoo2, Gon Khang1,*

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 45-57, 2021, DOI:10.32604/cmc.2020.013035

    Abstract Advances in the field of medical sciences and medical technology, and present-day challenges, such as an aging population, rising medical expenses, and lifestyle-related diseases, have collectively catalyzed a research ecosystem termed “smart wellness.” This article describes the establishment of a smart wellness service platform designed to empower individuals to create a sense of balance in their lives. Step-by-step details include service model, design, and architectural considerations. As a proof of concept, implementation details of a Health Improvement and Management Systems (HIMS) Hub, a Smart Wellness Service Platform deployed in six cities in South Korea, are presented. An on-site survey conducted… More >

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