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  • 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 - 30 October 2020

    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 >

  • 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 - 30 October 2020

    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 >

  • 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 - 30 October 2020

    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 >

  • Open Access

    ARTICLE

    On Modeling the Medical Care Insurance Data via a New Statistical Model

    Yen Liang Tung1, Zubair Ahmad2,*, G. G. Hamedani3

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 113-126, 2021, DOI:10.32604/cmc.2020.012780 - 30 October 2020

    Abstract Proposing new statistical distributions which are more flexible than the existing distributions have become a recent trend in the practice of distribution theory. Actuaries often search for new and appropriate statistical models to address data related to financial and risk management problems. In the present study, an extension of the Lomax distribution is proposed via using the approach of the weighted T-X family of distributions. The mathematical properties along with the characterization of the new model via truncated moments are derived. The model parameters are estimated via a prominent approach called the maximum likelihood estimation… 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 - 30 October 2020

    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 >

  • Open Access

    ARTICLE

    Exploring Views on Caregiving for Older Persons among Formal Social Care Workers in Malaysia: A Qualitative Study

    Halimatus Sakdiah Minhat1,2,*, Hazwan Mat Din1

    International Journal of Mental Health Promotion, Vol.22, No.4, pp. 283-290, 2020, DOI:10.32604/IJMHP.2020.012679 - 22 December 2020

    Abstract The rapid ageing process experienced by many developing countries, lead issues and challenges to deal with the highly demanding social care sector. This qualitative study aimed to explore the understanding and views of the formal caregivers in Malaysia towards social care for older persons. Series of focus group discussions were conducted among 57 institutional social care workers at four public residential care in Peninsular Malaysia based on the identified zones. Two groups of participants involved, those aged less than 40 years old and 40 years old and above, divided based on the mean age. The… More >

  • Open Access

    ARTICLE

    Internet of Things in Healthcare: Architecture, Applications, Challenges, and Solutions

    Vankamamidi S. Naresh1,∗,†, Suryateja S. Pericherla2,‡, Pilla Sita Rama Murty3,§, Sivaranjani Reddi4,¶

    Computer Systems Science and Engineering, Vol.35, No.6, pp. 411-421, 2020, DOI:10.32604/csse.2020.35.411

    Abstract Healthcare, the largest global industry, is undergoing significant transformations with the genesis of a new technology known as the Internet of Things (IoT). Many healthcare leaders are investing more money for transforming their services to harness the benefits provided by IoT, thereby paving the way for the Internet of Medical Things (IoMT), an extensive collection of medical sensors and associated infrastructure. IoMT has many benefits like providing remote healthcare by monitoring health vitals of patients at a distant place, providing healthcare services to elderly people, and monitoring a large group of people in a region 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 - 02 November 2020

    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 >

  • Open Access

    ARTICLE

    An Improved Crow Search Based Intuitionistic Fuzzy Clustering Algorithm for Healthcare Applications

    Parvathavarthini S1,*, 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 >

  • Open Access

    ARTICLE

    Effective and Efficient Ranking and Re-Ranking Feature Selector for Healthcare Analytics

    S.Ilangovan1,*, 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 >

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