K. V. Praveen¹, P. M. Joe Prathap², S. Dhanasekaran³, I. S. Hephzi Punithavathi⁴, P. Duraipandy⁵, Irina V. Pustokhina⁶, Denis A. Pustokhin^7,*

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.… More >

Ruben Willems^1,*, Fouke Ombelet², Eva Goossens^2,3,4, Katya De Groote⁵, Werner Budts^6,7, Stéphane Moniotte⁸, Michèle de Hosson⁹, Liesbet Van Bulck^2,4, Arianne Marelli¹⁰, Philip Moons^2,11,12, Julie De Backer^4,9,#, Lieven Annemans^1,#

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.… More >

Rizwan Ali Naqvi¹, Dildar Hussain², Woong-Kee Loh^3,*

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… More >

Sadaf Qazi¹, Muhammad Usman¹, Azhar Mahmood¹, Aaqif Afzaal Abbasi², Muhammad Attique³, Yunyoung Nam^4,*

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… More >

Gia Nhu Nguyen^1,2, Nin Ho Le Viet^1,2, Gyanendra Prasad Joshi³, Bhanu Shrestha^4,*

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 More >

Umar Farooq¹, Intae Ryoo², Gon Khang^1,*

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 More >

Parvathavarthini S^1,*, Karthikeyani Visalakshi N², Shanthi S³, Madhan Mohan J⁴

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 253-260, 2020, DOI:10.31209/2019.100000155

Abstract Intuitionistic fuzzy clustering allows the uncertainties in data to be represented more precisely. Medical data usually possess a high degree of uncertainty and serve as the right candidate to be represented as Intuitionistic fuzzy sets. However, the selection of initial centroids plays a crucial role in determining the resulting cluster structure. Crow search algorithm is hybridized with Intuitionistic fuzzy C-means to attain better results than the existing hybrid algorithms. Still, the performance of the algorithm needs improvement with respect to the objective function and cluster indices especially with internal indices. In order to address these More >

S.Ilangovan^1,*, A. Vincent Antony Kumar²

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 261-268, 2020, DOI:10.31209/2019.100000154

Abstract In this work, a Novel Feature selection framework called SU embedded PSO Feature Selector has been proposed (SU-PSO) towards the selection of optimal feature subset for the improvement of detection performance of classifiers. The feature space ranking is done through the Symmetrical Uncertainty method. Further, memetic operators of PSO include features and remove features are used to choose relevant features and the best of best features are selected using PSO. The proposed feature selector efficiently removes not only irrelevant but also redundant features. Performance metric such as classification accuracy, subset of features selected and running More >

Mònica Cunill¹, Maria Aymerich¹, Bernat-Carles Serdà^2,*, Josefina Patiño-Masó³

International Journal of Mental Health Promotion, Vol.22, No.3, pp. 185-198, 2020, DOI:10.32604/IJMHP.2020.011615

Abstract Aim: To describe the physical and psychological symptoms in healthcare workers caring for COVID-19 patients. Methods: Cross-sectional descriptive study design. A sample of 1,452 participants was collected. Sociodemographic data were recorded. Symptoms of anxiety were screened with Generalized Anxiety Disorder (GAD-7), symptoms of depression were measured with the Patient Health Questionnaire (PHQ-9), and finally physical symptoms were measured using the Patient Health Questionnaire (PHQ-15). Percentages, means and standard deviations, the one-way and two-way ANOVA test, the Chi square test and Pearson’s correlation coefficient were all calculated. The level of significance was (p < 0.05). Results: Medium levels… More >

Muhammad Adnan Khan^{1, *}, Sagheer Abbas², Ayesha Atta^{2, 3}, Allah Ditta⁴, Hani Alquhayz⁵, Muhammad Farhan Khan⁶, Atta-ur-Rahman⁷, Rizwan Ali Naqvi⁸

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 139-151, 2020, DOI:10.32604/cmc.2020.011416

Abstract The innovation in technologies related to health facilities today is increasingly helping to manage patients with different diseases. The most fatal of these is the issue of heart disease that cannot be detected from a naked eye, and attacks as soon as the human exceeds the allowed range of vital signs like pulse rate, body temperature, and blood pressure. The real challenge is to diagnose patients with more diagnostic accuracy and in a timely manner, followed by prescribing appropriate treatments and keeping prescription errors to a minimum. In developing countries, the domain of healthcare is… More >