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  • Open Access

    ARTICLE

    A Fractional-Order Machine Learning Framework for Modeling Vertebral Column Pathology and Biomechanical Dynamics

    David Amilo1,*, Khadijeh Sadri1, Evren Hincal1,2, Chinedu Izuchukwu3, Mohamed Hafez4,5, Muhammad Farman1,6,7, Kottakkaran Sooppy Nisar8,9

    CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.3, 2026, DOI:10.32604/cmes.2026.077921 - 30 June 2026

    Abstract Spinal disorders, such as disk hernia and spondylolisthesis, affect millions worldwide, leading to chronic pain and reduced quality of life due to disruptions in biomechanical alignment. Traditional diagnostic methods often overlook the viscoelastic memory effects in spinal tissues, necessitating advanced models that integrate machine learning with fractional calculus for improved accuracy and interpretability. The research introduces a new fractional-order machine learning system that analyzes vertebral column abnormalities through biomechanical motion analysis by using the University of California, Irvine (UCI) vertebral column dataset. The system selects the best machine learning model from Random Forest (RF), Gradient… More >

  • Open Access

    ARTICLE

    FedPA: Federated Learning with Performance-Based Averaging for Efficient Medical Image Classification

    Atif Mahmood1,*, Yasin Saleem1, Usman Tariq2, Yousef Ibrahim Daradkeh3, Adnan N. Qureshi4

    CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.3, 2026, DOI:10.32604/cmes.2025.073501 - 30 March 2026

    Abstract Federated learning is a decentralized model training paradigm with significant potential. However, the quality of Federated Network’s client updates can vary due to non-IID data distributions, leading to suboptimal global models. To address this issue, we propose a novel client selection strategy called FedPA (Performance-Based Federated Averaging). This proposed model selectively aggregates client updates based on a predefined performance threshold. Only clients whose local models achieve an F1 score of 70% or higher after training are included in the aggregation process. Clients below this threshold receive the updated global model but do not contribute their… More >

  • Open Access

    ARTICLE

    Social Value and Public Health: Exploring the Impact of Social Connection on the Community Mental Health

    Jimin Chae1, Youngbin Lym2,*, Geiguen Shin2,3,*

    International Journal of Mental Health Promotion, Vol.28, No.1, 2026, DOI:10.32604/ijmhp.2025.071482 - 28 January 2026

    Abstract Background: Social connection is widely recognized as a protective determinant of health, yet its direct and indirect effects on mental health remain underexplored. This study examines the relationship between social connection and mental health, focusing on the mediating role of quality of life (QoL) and the moderating effect of regional differences. Methods: We analyzed data from the 2019 Korean Community Health Survey, comprising 229,099 adults. Mental health was assessed through validated measures of depressive symptoms and psychological well-being. Social connection was measured using indicators of interpersonal ties and community participation, and QoL was assessed via self-reported… More >

  • Open Access

    ARTICLE

    Machine Learning Models for Predicting Smoking-Related Health Decline and Disease Risk

    Vaskar Chakma1,*, Md Jaheid Hasan Nerab1, Abdur Rouf1, Abu Sayed2, Hossem Md Saim3, Md. Nournabi Khan3

    Journal of Intelligent Medicine and Healthcare, Vol.4, pp. 1-35, 2026, DOI:10.32604/jimh.2026.074347 - 23 January 2026

    Abstract Smoking continues to be a major preventable cause of death worldwide, affecting millions through damage to the heart, metabolism, liver, and kidneys. However, current medical screening methods often miss the early warning signs of smoking-related health problems, leading to late-stage diagnoses when treatment options become limited. This study presents a systematic comparative evaluation of machine learning approaches for smoking-related health risk assessment, emphasizing clinical interpretability and practical deployment over algorithmic innovation. We analyzed health screening data from 55,691 individuals, examining various health indicators including body measurements, blood tests, and demographic information. We tested three advanced… More >

  • Open Access

    ARTICLE

    Public Health Implications of Road Construction and Traffic Congestion in a Hydrocarbon-Polluted Environment: An Assessment of Air and Noise Pollution

    Idongesit Sunday Ambrose1, Sunday Edet Etuk2, Okechukwu Ebuka Agbasi3,*, Ijah Ioryue Silas4, Unyime Udoette Saturday5, Eyo Edet Orok6

    Revue Internationale de Géomatique, Vol.34, pp. 335-350, 2025, DOI:10.32604/rig.2025.064552 - 13 June 2025

    Abstract Road construction and traffic congestion are increasingly recognized as major contributors to environmental and public health challenges in urban Nigeria, particularly in Rivers State. Despite growing urbanization, a gap remains in localized data on the combined effects of air and noise pollution in hydrocarbon-polluted environments. This study addresses that gap by conducting a preliminary environmental health assessment focused on the Port Harcourt Ring Road project. Air quality and noise levels were monitored in situ at 20 strategically selected locations, with five control points included for baseline comparison. Digital portable meters were used to measure concentrations of… More >

  • Open Access

    ARTICLE

    Generalized Anxiety Disorder Prevalence and Related Risk Factors among Females with Polycystic Ovarian Syndrome in Jazan Region, Saudi Arabia

    Abdullah A. Alharbi1, Ahmad Y. Alqassim1,*, Mohammad A. Jareebi1, Ahmad A. Alharbi2, Nada M. Makein1, Fatimah H. Al Ghazwi3, Seba Y. Muzaiiadi3, Joud N. Refaei3, Revan A. Arishi3, Bashaer A. Al Rajhi3, Fatima A. Aqili3, Saleha M. Ayoub3, Mohammed A. Muaddi1

    International Journal of Mental Health Promotion, Vol.27, No.5, pp. 701-716, 2025, DOI:10.32604/ijmhp.2025.062924 - 05 June 2025

    Abstract Background: Polycystic ovarian syndrome (PCOS), a common endocrine disorder in reproductive-aged women, has substantial physical and psychological impacts. While the physical manifestations of PCOS are well established, the psychological burden, especially anxiety, is understudied in Saudi Arabia. This study aimed to assess the prevalence of generalized anxiety disorder among females with PCOS compared to those without PCOS, and to identify the clinical and sociodemographic factors associated with anxiety in the Jazan region of Saudi Arabia. Methods: A cross-sectional study was conducted between January and March 2023 using an Arabic self-administered online questionnaire distributed via social… More >

  • Open Access

    REVIEW

    Leveraging Artificial Intelligence to Achieve Sustainable Public Healthcare Services in Saudi Arabia: A Systematic Literature Review of Critical Success Factors

    Rakesh Kumar1,*, Ajay Singh2, Ahmed Subahi Ahmed Kassar3, Mohammed Ismail Humaida3, Sudhanshu Joshi4, Manu Sharma5

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1289-1349, 2025, DOI:10.32604/cmes.2025.059152 - 27 January 2025

    Abstract This review aims to analyze the development and impact of Artificial Intelligence (AI) in the context of Saudi Arabia’s public healthcare system to fulfill Vision 2030 objectives. It is extensively devoted to AI technology deployment relevant to disease management, healthcare delivery, epidemiology, and policy-making. However, its AI is culturally sensitive and ethically grounded in Islam. Based on the PRISMA framework, an SLR evaluated primary academic literature, cases, and practices of Saudi Arabia’s AI implementation in the public healthcare sector. Instead, it categorizes prior research based on how AI can work, the issues it poses, and… More >

  • Open Access

    ARTICLE

    Linking Perceived Risk of Public Health Emergency to Psychological Distress among Chinese College Students: The Chain Mediation Role of Balanced Time Perspective and Negative Coping Styles

    Biru Chang1,*, Shengqiang Zhu2, Qian Xie3,4, Yanghui Dai5

    International Journal of Mental Health Promotion, Vol.26, No.8, pp. 599-610, 2024, DOI:10.32604/ijmhp.2024.050302 - 30 August 2024

    Abstract Background: With public health emergencies (PHE) worldwide increasing, the perceived risk of PHE has been one of the critical factors influencing college students’ psychological distress. However, the mechanisms by which the perceived risk of PHE affects college students’ psychological distress are not clear. The study’s purpose was to investigate the mediation roles of deviation from a balanced time perspective (DBTP) and negative coping styles between the perceived risk of PHE and psychological distress. Methods: A convenience sampling method was used to survey 1054 Chinese college students with self-reporting. Data was collected using the Public Risk… More >

  • Open Access

    ARTICLE

    Exploring the Prevalence and Contributing Factors of Depression among Sickle Cell Anemia Patients in Saudi Arabia’s Jazan Region

    Abdullah A. Alharbi1, Ahmad Y. Alqassim1,*, Mohammed A. Muaddi1, Najat H. Aldubayyan1, Rana I. Abuhadi1, Futon A. Akoor1, Sarah J. Mobarki1, Imtenan A. Oberi1, Ghaidaa H. Alharbi1, Yara Ajeebi1, Adnan M. Alkhayat2, Hafiz Malhan3, Mohammed Bakkar4, Anwar M. Makeen1

    International Journal of Mental Health Promotion, Vol.26, No.5, pp. 351-359, 2024, DOI:10.32604/ijmhp.2024.047219 - 30 May 2024

    Abstract Sickle Cell Anemia (SCA) is a prevalent genetic condition in Saudi Arabia, particularly in the Jazan region. The study’s purpose was to assess the prevalence of de-pression among individuals with SCA in this area and to identify the factors associated with this condition. The study involved 391 adult participants, all patients in the hematology center of Prince Mohammed bin Nasser Hospital (PMNH). Data was collected through an anonymous interview questionnaire–the Arabic version of the Patient Health Questionnaire-9 (PHQ-9)–between March–May 2022. The questionnaire covered socio-demographic information and variables related to the participant’s SCA history, such as… More >

  • Open Access

    ARTICLE

    Analyzing COVID-19 Discourse on Twitter: Text Clustering and Classification Models for Public Health Surveillance

    Pakorn Santakij1, Samai Srisuay2,*, Pongporn Punpeng1

    Computer Systems Science and Engineering, Vol.48, No.3, pp. 665-689, 2024, DOI:10.32604/csse.2024.045066 - 20 May 2024

    Abstract Social media has revolutionized the dissemination of real-life information, serving as a robust platform for sharing life events. Twitter, characterized by its brevity and continuous flow of posts, has emerged as a crucial source for public health surveillance, offering valuable insights into public reactions during the COVID-19 pandemic. This study aims to leverage a range of machine learning techniques to extract pivotal themes and facilitate text classification on a dataset of COVID-19 outbreak-related tweets. Diverse topic modeling approaches have been employed to extract pertinent themes and subsequently form a dataset for training text classification models.… More >

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