Detection of Malicious Clients in Federated Learning Using Graph Neural Network by Anee Sharma, Ningrinla Marchang

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Knowledge, Attitudes, and Perceptions of Chronic Patients in Saudi Arabia Regarding the Use of Artificial Intelligence to Improve Medication Adherence by Alsanosi SM, Aldajani AQ, Gheliwi HA, Alotibi MM, Bokhari GS, Almatrafi OA, Alqawlaq AK, Abujamai JZ, Shaikhomer M, Alhindi YZ, Alshanberi AM

“…Safaa M Alsanosi,1 Asayel Q Aldajani,2 Hasnaa A Gheliwi,2 Manar M Alotibi,2 Ghadi S Bokhari,2 Orjuwan A Almatrafi,2 Abdulelah K Alqawlaq,3 Jakleen Z Abujamai,3 Mohammed Shaikhomer,4 Yosra Z Alhindi,1 Asim M Alshanberi3 1Department of Pharmacology and Toxicology, Faculty of Medicine, Umm Al Qura University, Makkah, Saudi Arabia; 2Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia; 3General Medicine Program, Batterjee Medical College, Jeddah, Saudi Arabia; 4Department of Internal Medicine, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi ArabiaCorrespondence: Safaa M Alsanosi, Department of Pharmacology and Toxicology, Faculty of Medicine, Umm Al Qura University, Makkah, Saudi Arabia, Email smsanosi@uqu.edu.saBackground: Artificial intelligence (AI) is advancing healthcare globally and in Saudi Arabia, enhancing patient care, diagnostics, and administrative efficiency, despite challenges such as data privacy and regulation. This study explores knowledge, attitudes, and perceptions (KAP) regarding AI in medication adherence among chronic patients in Makkah region, Saudi Arabia.Methods: A cross-sectional study was conducted among patients with chronic diseases in the Makkah region, Saudi Arabia, from 1 July to 31 December 2024. …”
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Prevalence of adolescent dual tobacco use and its associated factors: findings from a cross-sectional study by Mohd Firdaus Razali, Mohd Ruhaizie Riyadzi, Hamizatul Akmal Abd Hamid, Khaw Wan-Fei, Ummi Nadiah Yusoff

“…Objective To determine the prevalence and its associated factors of dual tobacco use among Malaysian adolescents in developing effective public health strategies.Design Cross-sectional study.Setting This study analysed data from the National Health and Morbidity Survey (NHMS) 2022: Adolescent Health Survey (AHS), a nationwide cross-sectional survey conducted among secondary school students across Malaysia.Participants This cross-sectional study used data from the NHMS 2022: AHS, which included a representative national sample of Malaysian adolescents between the ages of 13 and 17. …”
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SMS spam detection using BERT and multi-graph convolutional networks by Linjie Shen, Yanbin Wang, Zhao Li, Wenrui Ma

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“When he is around, I’ll take the PrEP, but when he is not, I will not take PrEP”: key influences on PrEP use decisions among women attending family planning clinics in Kenya by Vallery Ogello, Kristin Beima-Sofie, Sandra Urusaro, Mercy Awuor, Annabell Dollah, Winnie Atieno, Cynthia Wandera, Daniel Matemo, Jennifer F. Morton, Kenneth Ngure, Kenneth Ngure, John Kinuthia, John Kinuthia, Kenneth K. Mugwanya, Kenneth K. Mugwanya

“…Participants expressed a preference for alternative PrEP formulations, such as injectable PrEP, due to perceived ease of use, privacy, and potential to support adherence.ConclusionPrEP discontinuation and restart cycles largely reflected changes in HIV risk. …”
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Health Care Professionals’ Use of Digital Technology in the Secondary Prevention of Cardiovascular Disease in Austria: Online Survey Study by Luisa Lunz, Sabine Würth, Stefan Tino Kulnik

“…Quantitative survey data were analyzed using descriptive statistics, group comparison tests, and association statistics. …”
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Building occupancy estimation using single channel CW radar and deep learning by Sourav Kumar Pramanik, Md. Shafkat Hossain, Shekh Md. Mahmudul Islam

“…Unlike previous studies that rely on WiFi or PIR-based sensors, this approach provides a robust alternative without privacy concerns. The time-frequency scalograms generated from radar echoes were used to train deep-learning models, including DarkNet19, MobileNetV2, and ResNet18. …”
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A content review of COVID-19-related apps used in Vietnam by Linh Tran, Federica Cucé, Nguyen Thanh An, Kadek Agus Surya Dila, Nguyen Hai Nam, Doan Le Nguyet Cat, Lee Wei Jun, Farrukh Ansar, Fatima Abdallh, Au Vo, Nguyen Tien Huy

“…The most serious user concerns were privacy breaches during data recording and storage, technical issues, and non-user-friendly interfaces. …”
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Blockchain framework with IoT device using federated learning for sustainable healthcare systems by B. Bhasker, P. Muralidhara Rao, P. Saraswathi, S. Gopal Krishna Patro, Javed Khan Bhutto, Saiful Islam, Mohammed Kareemullah, Addisu Frinjo Emma

“…The proposed method achieves data privacy and security by 98.73%, intrusion detection efficiency by 97.16%, disease detection accuracy by 96.425, proactive healthcare management by 98.37%, and interoperability by 96.74%.…”
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Unobtrusive stress detection using wearables: application and challenges in a university setting by Peter Neigel, Andrew Vargo, Benjamin Tag, Koichi Kise

“…Advances in sensing accuracy and utility design in wearables might make this feasible; however, real-world adoption faces challenges, as users often fail to wear or use these devices consistently and correctly. Additionally, institutional monitoring raises privacy concerns.MethodsIn this study, we analyze real-world data from a cohort of 103 Japanese university students to identify periods of cyclical stress while ensuring individual privacy through aggregation. …”
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Cancelable finger vein authentication using multidimensional scaling based on deep learning by Mohamed Hammad, Mohammed ElAffendi, Ahmed A. Abd El-Latif

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Using social presence theory to predict online consumer engagement in the emerging markets by Abraham Yeboah, Ofosu Agyekum, Vida Owusu-Prempeh, Kwadwo Boateng Prempeh

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Heartbeat detection and personal authentication using a 60 GHz Doppler sensor by Takuma Asano, Shintaro Izumi, Hiroshi Kawaguchi

“…Unlike fingerprint and facial recognition systems, they offer authentication without physical contact or privacy concerns. This study focuses on non-contact seismocardiography using microwave Doppler sensors and aims to apply this technology for biometric authentication.MethodWe proposed a method for authenticating and identifying heartbeat signals through supervised learning using a conditional variational autoencoder (CVAE). …”
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Emotion Estimation Using Noncontact Environmental Sensing with Machine and Deep Learning Models by Tsumugi Isogami, Nobuyoshi Komuro

“…This paper presents a method for estimating arousal and emotional valence levels using non-contact environmental sensing, addressing challenges such as discomfort from long-term device wear and privacy concerns associated with facial image analysis. …”
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Using Digital Technology to Conduct COVID-19 Surveillance: A Systematic Review by Fitrisia Rahma, Fatmah Fatmah, Rachmadhi Purwana

“…Unique Contribution: This study emphasises the role of digital technologies in virus detection, monitoring, and prevention as a medium of infectious disease transmission, particularly in contact tracing, symptom monitoring, location tracking, and real-time data management. It highlights the challenges of privacy, data security, and public adoption issues. …”
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Development of an intelligent intrusion detection system for IoT networks using deep learning by Haozhe Zhang

“…However, attack diversity, device heterogeneity, and traditional security limitations necessitate advanced data analysis. Researchers increasingly use deep learning, which excels in handling large-scale data, to develop robust intrusion detection systems. …”
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High-fidelity steganography in EEG signals using advanced transform-based methods by Enes Efe

“…The increasing prevalence of digital health solutions and smart health devices (SHDs) ensures the continuity of personal biometric data while simultaneously raising concerns about their security and privacy. …”
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Healthcare Professionals' Views on the Use of Passive Sensing and Machine Learning Approaches in Secondary Mental Healthcare: A Qualitative Study by Jessica Rogan, Joseph Firth, Sandra Bucci

“…Interview data were analysed using reflexive thematic analysis. …”
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Bioethical implications of the use of digital technologies for mental health research during the social distancing period of the COVID-19 pandemic by Liliana Mondragón-Barrios, Gabriela Martínez-Levy, Adriana Díaz-Anzaldúa, Miguel Ángel Caballero-Gutiérrez, Luis Moncayo-Samperio

“…The need to apply ethical principles to protocols for mental health research using digital technologies was a central concern of ethics committees during the COVID-19 pandemic, which sought to ensure a fair selection of participants, appropriate adaptation of the informed consent process, protection of participants’ privacy, secure management of research data, and assessment of risks and benefits. …”
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Security of medical images over insecure communication channels using zero-steganography by Wadood Abdul

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