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  • Open Access


    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


    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


    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 >

  • Open Access


    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 issues, the crow search algorithm… More >

  • Open Access


    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 time are used for comparison. More >

  • Open Access


    The Impact of COVID-19 on Spanish Health Professionals: A Description of Physical and Psychological Effects

    Mònica Cunill1, Maria Aymerich1, Bernat-Carles Serdà2,*, 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 of anxiety (range,… More >

  • Open Access


    Intelligent Cloud Based Heart Disease Prediction System Empowered with Supervised Machine Learning

    Muhammad Adnan Khan1, *, Sagheer Abbas2, Ayesha Atta2, 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 progressing day by day using… More >

  • Open Access


    Italian Validation of the Healthcare Needs Scale for Youth with Congenital Heart Disease and Its Short-Form Development

    Federica Dellafiore1, Serena Francesca Flocco1, Cristina Arrigoni2, Serena Barello3, Tiziana Nania1, Maria Giovanna Russo4, Berardo Sarubbi5, Arianna Magon1, Francesco Pittella1, Massimo Chessa6, Rosario Caruso1,*

    Congenital Heart Disease, Vol.15, No.3, pp. 167-180, 2020, DOI:10.32604/CHD.2020.012438

    Abstract Aims: This study aimed at providing an Italian short version of the ‘healthcare needs scale for youth with congenital heart disease’ (I-HNS-CHD-s), describing its construct validity and reliability. Methods: A multi-method and multi-phase design were adopted. Phase one referred to the cultural-linguistic validation of the original scale into Italian. Phase two tasted content and face validity of the Italian-translated scale. Phase three included the psychometric validation process of scale, encompassed two different steps: first cross-sectional data collection (sample A) purposed at determining the psychometric characteristics of the I-HNS-CHD-s, using an exploratory factor analysis (EFA). Then, a second round of cross-sectional… More >

  • Open Access


    Preparing adolescents with heart problems for transition to adult care, 2009–2010 National Survey of Children with Special Health Care Needs

    Karrie F. Downing1,2, Matthew E. Oster1,3, Sherry L. Farr1

    Congenital Heart Disease, Vol.12, No.4, pp. 497-506, 2017, DOI:10.1111/chd.12476

    Abstract Objective: A substantial percentage of children with congenital heart disease (CHD) fail to transfer to adult care, resulting in increased risk of morbidity and mortality. Transition planning discussions with a provider may increase rates of transfer, yet little is known about frequency and content of these discussions. We assessed prevalence and predictors of transition-related discussions between providers and parents of children with special healthcare needs (CSHCN) and heart problems, including CHD.
    Design: Using parent-reported data on 12- to 17-year-olds from the 2009–2010 National Survey of CSHCN, we calculated adjusted prevalence ratios (aPR) for associations between demographic factors and provider discussions… More >

  • Open Access


    Current trends in racial, ethnic, and healthcare disparities associated with pediatric cardiac surgery outcomes

    Jennifer K. Peterson1, Yanjun Chen2, Danh V. Nguyen3, Shaun P. Setty1

    Congenital Heart Disease, Vol.12, No.4, pp. 520-532, 2017, DOI:10.1111/chd.12475

    Abstract Objective: Despite overall improvements in congenital heart disease outcomes, racial and ethnic disparities have continued. The purpose of this study is to examine the effect of race and ethnicity, as well as other risk factors on congenital heart surgery length of stay and in-hospital mortality.
    Design: From the 2012 Healthcare Cost and Utilization Project Kids Inpatient Database (KID), we identified 13 130 records with Risk Adjustment in Congenital Heart Surgery complexity scoreeligible procedures. Multivariate logistic and linear regression modeling with survey weights, stratification and clustering was used to examine the relationships between predictor variables and length of stay as well… More >

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