Yingfeng Wang^*

International Journal of Mental Health Promotion, Vol.25, No.10, pp. 1159-1159, 2023, DOI:10.32604/ijmhp.2023.046109

Abstract This article has no abstract. More >

Firas Abedi¹, Hayder M. A. Ghanimi², Abeer D. Algarni³, Naglaa F. Soliman^3,*, Walid El-Shafai^4,5, Ali Hashim Abbas⁶, Zahraa H. Kareem⁷, Hussein Muhi Hariz⁸, Ahmed Alkhayyat⁹

Computer Systems Science and Engineering, Vol.47, No.3, pp. 2791-2814, 2023, DOI:10.32604/csse.2023.038762

Abstract Data mining plays a crucial role in extracting meaningful knowledge from large-scale data repositories, such as data warehouses and databases. Association rule mining, a fundamental process in data mining, involves discovering correlations, patterns, and causal structures within datasets. In the healthcare domain, association rules offer valuable opportunities for building knowledge bases, enabling intelligent diagnoses, and extracting invaluable information rapidly. This paper presents a novel approach called the Machine Learning based Association Rule Mining and Classification for Healthcare Data Management System (MLARMC-HDMS). The MLARMC-HDMS technique integrates classification and association rule mining (ARM) processes. Initially, the chimp optimization algorithm-based feature selection (COAFS)… More >

Nojood O Aljehane^*

Computer Systems Science and Engineering, Vol.47, No.3, pp. 3109-3126, 2023, DOI:10.32604/csse.2023.038042

Abstract Medical image analysis is an active research topic, with thousands of studies published in the past few years. Transfer learning (TL) including convolutional neural networks (CNNs) focused to enhance efficiency on an innovative task using the knowledge of the same tasks learnt in advance. It has played a major role in medical image analysis since it solves the data scarcity issue along with that it saves hardware resources and time. This study develops an Enhanced Tunicate Swarm Optimization with Transfer Learning Enabled Medical Image Analysis System (ETSOTL-MIAS). The goal of the ETSOTL-MIAS technique lies in the identification and classification of… More >

Zuriati Ahmad Zukarnain^1,*, Amgad Muneer^2,3, Nur Atirah Mohamad Nassir¹, Akram A. Almohammedi^4,5

Computer Systems Science and Engineering, Vol.47, No.3, pp. 2725-2740, 2023, DOI:10.32604/csse.2023.034448

Abstract With the advancements in the era of artificial intelligence, blockchain, cloud computing, and big data, there is a need for secure, decentralized medical record storage and retrieval systems. While cloud storage solves storage issues, it is challenging to realize secure sharing of records over the network. Medi-block record in the healthcare system has brought a new digitalization method for patients’ medical records. This centralized technology provides a symmetrical process between the hospital and doctors when patients urgently need to go to a different or nearby hospital. It enables electronic medical records to be available with the correct authentication and restricts… More >

Sidra Abbas¹, Gabriel Avelino Sampedro^2,3, Shtwai Alsubai⁴, Ahmad Almadhor⁵, Tai-hoon Kim^6,*

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 665-680, 2023, DOI:10.32604/cmc.2023.041031

Abstract Cardiac disease is a chronic condition that impairs the heart’s functionality. It includes conditions such as coronary artery disease, heart failure, arrhythmias, and valvular heart disease. These conditions can lead to serious complications and even be life-threatening if not detected and managed in time. Researchers have utilized Machine Learning (ML) and Deep Learning (DL) to identify heart abnormalities swiftly and consistently. Various approaches have been applied to predict and treat heart disease utilizing ML and DL. This paper proposes a Machine and Deep Learning-based Stacked Model (MDLSM) to predict heart disease accurately. ML approaches such as eXtreme Gradient Boosting (XGB),… More >

Fadhil Mukhlif^1,*, Norafida Ithnin¹, Roobaea Alroobaea², Sultan Algarni³, Wael Y. Alghamdi², Ibrahim Hashem⁴

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 583-599, 2023, DOI:10.32604/cmc.2023.038757

Abstract The World Health Organization (WHO) refers to the 2019 new coronavirus epidemic as COVID-19, and it has caused an unprecedented global crisis for several nations. Nearly every country around the globe is now very concerned about the effects of the COVID-19 outbreaks, which were previously only experienced by Chinese residents. Most of these nations are now under a partial or complete state of lockdown due to the lack of resources needed to combat the COVID-19 epidemic and the concern about overstretched healthcare systems. Every time the pandemic surprises them by providing new values for various parameters, all the connected research… More >

Amy J. Kaye^1,*, Vanessa Prosper², Kathryn Moffa¹, Vanja Pejic¹, Karen Capraro¹, Georgios D. Sideridis¹, Abigail Ross^1,3, Kristine M. Dennery¹, David R. DeMaso¹

International Journal of Mental Health Promotion, Vol.25, No.10, pp. 1103-1115, 2023, DOI:10.32604/ijmhp.2023.030185

Abstract The objective of this study was to evaluate the impact of Break Free from Depression (BFFD), a school-based depression awareness curriculum, in comparison to a wait list control group. A total of 13 eighth grade classrooms participated in either an intervention or control group and completed pre-, post-, and three-month follow-up surveys. Students participating in BFFD (N = 6 classrooms, 166 students) demonstrated enhanced knowledge of and more adaptive attitudes towards depression compared to the control group (N = 7 classrooms, 155 students). Participants in the BFFD intervention also demonstrated increases in their confidence in knowing how to seek help… More >

Sándor Csibi¹, Mónika Csibi^2,*, József Bognár¹

International Journal of Mental Health Promotion, Vol.25, No.10, pp. 1081-1088, 2023, DOI:10.32604/ijmhp.2023.029390

Abstract Background: Components of Self, completed with the perceived social support determine the individual differences in the evaluation of a stressor and the behavioral responses toward it, such as health-related anxiety. The study set as a goal the analysis of associations between the components of Self, such as self-evaluation, sense of coherence, perceived social support, and reported health-related anxiety in an adult sample. Methods: 147 adults from the 18–73 age group (mean age 37.5) voluntarily completed the questionnaire through Qualtrics online platform containing the Short Health Anxiety Inventory, Core Self-Evaluation Scale, Social Support Assessing Scale, and one Health Self-Evaluation Item. Results:… More >

Namyun Kil^1,*, Jin Gun Kim², Emily Thornton¹, Amy Jeranek³

International Journal of Mental Health Promotion, Vol.25, No.10, pp. 1117-1125, 2023, DOI:10.32604/ijmhp.2023.022981

Abstract

Mental health conditions in children and adolescents can be improved by slow mindful nature connection known as forest therapy or bathing. Forest therapy has recently received growing attention as an enabler of relaxation and preventive health care with demonstrated clinical efficacy. However, it is not well-known that forest therapy also decreases mental health issues among individuals with mental health disorders. This study explored the psychological and physiological health benefits of structured forest therapy programs for children and adolescents with mental health disorders. A one-group pre-test-posttest design was employed for our study participants. Twelve participants (aged 9–14 years) engaged in two… More >

Naveed Khan¹, Jianbiao Zhang^1,*, Ghulam Ali Mallah², Shehzad Ashraf Chaudhry³

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3877-3896, 2023, DOI:10.32604/cmc.2023.032553

Abstract The mobile cellular network provides internet connectivity for heterogeneous Internet of Things (IoT) devices. The cellular network consists of several towers installed at appropriate locations within a smart city. These cellular towers can be utilized for various tasks, such as e-healthcare systems, smart city surveillance, traffic monitoring, infrastructure surveillance, or sidewalk checking. Security is a primary concern in data broadcasting, particularly authentication, because the strength of a cellular network’s signal is much higher frequency than the associated one, and their frequencies can sometimes be aligned, posing a significant challenge. As a result, that requires attention, and without information authentication, such… More >