Trends and pattern of contraceptive use among women attending a family planning clinic at a tertiary health facility in Ibadan, Nigeria by A. O. Atoyebi, S. O. Olaoye, M. A. Okunlola, M. E. Palamuleni, A. S. Adebowale

“…Data were analysed using a logistic regression model (α0.05), and thematic analysis was used for the qualitative part of the study. …”
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Understanding user acceptance of mobility-as-a-service in Jakarta Metropolitan Area (JMA): Influencing factors and behavioural insights by Yos Sunitiyoso, Prawira Fajarindra Belgiawan, Muhamad Rizki, Valid Hasyimi

“…Driven by theoretical constructs of the technology acceptance model, a set of motivational factors and choice scenarios, a behavioural model is conceptualised to explore individuals’ willingness to adopt MaaS in the JMA. Using data from 1,005 respondents collected in a survey, structural equation modelling (SEM), cluster analysis and choice modelling were conducted. …”
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Evaluation of privacy protection methods of public service advertising visual design in the perspective of artificial intelligence internet of things. by Xujun Tang

“…The digital watermark privacy protection method and the public service advertising work push privacy protection method are used to provide an innovative solution for public service advertising privacy protection. …”
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Collaborative and privacy-preserving cross-vendor united diagnostic imaging via server-rotating federated machine learning by Hao Wang, Xiaoyu Zhang, Xuebin Ren, Zheng Zhang, Shusen Yang, Chunfeng Lian, Jianhua Ma, Dong Zeng

“…Additionally, the communication protocol of SRFLM provides strong privacy guarantees using differential privacy. We extensively evaluate SRFLM across multiple cross-vendor diagnostic imaging tasks. …”
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PLASMA-Privacy-Preserved Lightweight and Secure Multi-level Authentication scheme for IoMT-based smart healthcare by Hegde Manjunath, M. Karthik, Hegde Varun, Rao Rohini R., Mantoor Vinayak M., Bhat Radhakrishna

“…PLASMA’s security and key privacy are validated through the Real-Or-Random (ROR) model and simulated using the widely accepted Scyther tool. …”
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Leveraging Complex-Valued Federated Learning for Accurate and Privacy-Respectful Threat Detection Based on Millimeter-Wave Imaging by Hadi Mahdipour, Jaime Laviada, Fernando Las-Heras Andres, Mehdi Sookhak

“…This approach provides a highly accurate and privacy-preserving solution for CO detection using high-resolution MMW radar. …”
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Privacy-Preserving Federated Learning in Healthcare, E-Commerce, and Finance: A Taxonomy of Security Threats and Mitigation Strategies by Kumar Rahul, Shieh Chin-Shiuh, Chakrabarti Prasun, Kumar Ashok, Moolchandani Jhankar, Sinha Raj

“…Federated Learning (FL) transformed decentralized machine learning by allowing joint model training without mutually sharing raw data, hence being especially useful in privacy-sensitive applications like healthcare, e-commerce, and finance. …”
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Harnessing Artificial Intelligence to Transform Education: Challenges and Opportunities by Ahma Greta, Kadriu Arbana

“…These include worries about algorithmic unfairness, data privacy, and teachers’ or students’ resistance to using AI-based solutions. …”
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Optimizing malicious website prediction: An advanced XGBoost-based machine learning model by Hussain Sumaira, Zada Islam, Alazab Moutaz, Alfraihi Hessa, Aldhayan Manal, Ullah Inam, Khan Mohammad Asmat Ullah

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Federated Deep Learning for Scalable and Privacy-Preserving Distributed Denial-of-Service Attack Detection in Internet of Things Networks by Abdulrahman A. Alshdadi, Abdulwahab Ali Almazroi, Nasir Ayub, Miltiadis D. Lytras, Eesa Alsolami, Faisal S. Alsubaei, Riad Alharbey

“…ResNet improves feature extraction, VGGNet optimises feature refining, and Swin-Transformer captures contextual dependencies, making the model sensitive to complicated attack patterns across varied network circumstances. Using the FL framework, decentralised training protects data privacy and scales and adapts across diverse IoT contexts. …”
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Online fashion consumerism among women: The interplay of digital experiences and decision-making – a mediated moderated analysis by Madhura K., Niyaz Panakaje, S. M. Riha Parvin, Shakira Irfana, Mural Henrita Cutinha, Yatheen A, Rovina Sharon Soans

“…However, challenges like concerns over data privacy and difficulties in verifying review authenticity negatively affect the attitude-behavior relationship, with a moderating effect of β = -0.092. …”
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Federated Learning for Surface Roughness by Kai-Lun Cheng, Yu-Hung Ting, Wen-Ren Jong, Shia-Chung Chen, Zhe-Wei Zhou

“…A custom data acquisition system collected discharge current and spindle current signals, which were solely used as input features to train the deep learning model. …”
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“Crying in the Wilderness”—The Use of Web-Based Support in Telomere Biology Disorders: Thematic Analysis by Emily Eidenier Pearce, Alina Majid, Toniya Brown, Rowan Forbes Shepherd, Camella Rising, Catherine Wilsnack, Ashley S Thompson, Melissa B Gilkey, Kurt M Ribisl, Allison J Lazard, Paul KJ Han, Allison Werner-Lin, Sadie P Hutson, Sharon A Savage

“…Participants found web-based resources useful for information-seeking but reported privacy concerns and frustration with forming supportive relationships. …”
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Perceptions of, Barriers to, and Facilitators of the Use of AI in Primary Care: Systematic Review of Qualitative Studies by Héctor Martínez-Martínez, Julia Martínez-Alfonso, Belén Sánchez-Rojo-Huertas, Valeria Reynolds-Cortez, Andrea Turégano-Chumillas, Victoria A Meseguer-Ruiz, Shkelzen Cekrezi, Vicente Martínez-Vizcaíno

“…We identified four analytical themes using thematic synthesis: (1) change in the physician-patient relationship, highlighting concerns about loss of empathy, connection, and trust; (2) AI as a partner for efficient time and information management, including its potential to improve workflow and decision-making, alongside skepticism about increased workload; (3) data as the cornerstone of AI development, reflecting concerns about data privacy, quality, bias, and corporate responsibility; and (4) barriers to and facilitators of AI in primary care, emphasizing equity, accessibility, and stakeholder co-design. …”
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Social media and internet use among orthopedic patients in Germany—a multicenter survey by Yasmin Youssef, Tu-Lan Vu-Han, Tu-Lan Vu-Han, Richard Trauth, Georg Osterhoff, David Alexander Back, Tobias Gehlen, Tobias Gehlen

“…There is limited data regarding which SM orthopedic patients use and what benefits and risks of SM they perceive.MethodsAn online survey was conducted from April to December 2023 among orthopedic and trauma patients in five German orthopedic clinics. …”
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Consumer opinion on the use of machine learning in healthcare settings: A qualitative systematic review by Jacqueline H Stephens, Celine Northcott, Brianna F Poirier, Trent Lewis

“…The meta-synthesis identified four overarching themes across the included studies: (1) Trust, fear, and uncertainty; (2) Data privacy and ML governance; (3) Impact on healthcare delivery and access; and (4) Consumers want to be engaged. …”
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Policy guidelines and recommendations on AI use in teaching and learning: A meta-synthesis study by Aaron A. Funa, Renz Alvin E. Gabay

“…Under the theme of policies and guidelines, notable subthemes include ethical AI use, AI literacy, and inclusivity and equity. In terms of implementation strategies, the synthesis identifies crucial areas such as student orientation and professional development, enhanced teaching tools and data-driven insights, improved student learning outcomes and engagement, and streamlined administrative processes. …”
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Balancing risks and benefits: clinicians’ perspectives on the use of generative AI chatbots in mental healthcare by Lyndsey Hipgrave, Jessie Goldie, Simon Dennis, Simon Dennis, Amanda Coleman

“…However, they also identified risks, including the lack of regulation, data and privacy concerns, chatbots' limited understanding of client backgrounds, potential for client over-reliance on chatbots, incorrect treatment recommendations, and the inability to detect subtle communication cues, such as tone and eye contact. …”
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What patients and caregivers want to know when consenting to the use of digital behavioral markers by Anika Sonig, Christine Deeney, Meghan E. Hurley, Eric A. Storch, John Herrington, Gabriel Lázaro-Muñoz, Casey J. Zampella, Birkan Tunc, Julia Parish-Morris, Jenny Blumenthal-Barby, Kristin Kostick-Quenet

“…We observed seven key domains (in order of salience) in stakeholders’ informational needs: (1) clinical utility and value; (2) evidence, explainability, evaluation and contestation; (3) accuracy and trustworthiness; (4) data security, privacy, and misuse; (5) patient consent, control, and autonomy; (6) physician-patient relationship; and (7) patient safety, well-being, and dignity. …”
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Anonymization in web auctions using Zero-Knowledge Proof in Blockchain technology by Marlena Broniszewska, Wiktor B. Daszczuk, Denny B. Czejdo

“…However, the centralized nature of traditional e-commerce platforms raises concerns about data control, privacy, and potential single points of failure. …”
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