A comprehensive survey on AI-enabled secure social industrial Internet of Things in the agri-food supply chain by Sajal Halder, Md Rafiqul Islam, Quazi Mamun, Arash Mahboubi, Patrick Walsh, Md Zahidul Islam

“…The findings indicate that AI-driven security solutions significantly enhance trust management, anomaly detection, and data privacy in SIIoT networks. The proposed taxonomy categorizes AI-enabled security mechanisms into five distinct areas, offering a structured reference for future research and practical implementations. …”
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Advancing Healthcare: Intelligent Speech Technology for Transcription, Disease Diagnosis, and Interactive Control of Medical Equipment in Smart Hospitals by Ahmed Elhadad, Safwat Hamad, Noha Elfiky, Fulayjan Alanazi, Ahmed I. Taloba, Rasha M. Abd El-Aziz

“…The federated learning framework enabled collaborative model training across multiple hospital sites, preserving patient privacy by avoiding raw data exchange. This distributed approach allowed the model to learn from diverse, real-world data while ensuring compliance with strict data protection standards. …”
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Developing an artificial intelligence-based progressive growing GAN for high-quality facial profile generation and evaluation through turing test and aesthetic analysis by Shahab Kavousinejad, Kazem Dalaie, Mohammad Behnaz, Soodeh Tahmasbi, Asghar Ebadifar, Hoori Mirmohammadsadeghi

“…This approach offers valuable applications in orthodontic education, treatment simulation, and data augmentation, particularly where patient privacy and dataset balance are critical. …”
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Hybrid Convolutional Neural Network-Based Intrusion Detection System for Secure IoT Networks by Sami Qawasmeh, Ahmad Habboush, Bassam Elzaghmouri, Qasem Kharma, Da'ad Albalawneh

“…The training model defines the convolutional layer's structure, sliding window size, neuron connection weights, and outputs using the improved data. The training period is used for attack detection, and the weights are calculated from trained and real-time data. …”
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Exploring Respectful Maternity Care and its determinants: a mixed methods cross-sectional study from a rural area in central India by Chullithala Athira, Anindo Majumdar, Roshan F. Sutar, Bharti Singh, Parvathy Thampy, Ashlesh Rupani, Deepti Dabar

“…Descriptive data is presented in frequency tables. Quantitative data were analyzed using logistic regression and qualitative data through thematic analysis. …”
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A Blockchain-Based E-Participation Framework Utilizing Zero-Knowledge Proofs With Guaranteed Sampling and Differential Reward Mechanisms by Jungwon Seo, Juhui Lee, Yunjae Joo, Kangho Lee, Vijayan Sugumaran, Sooyong Park

“…Blockchain-based E-participation systems significantly enhance transparency, data integrity, and security compared to traditional E-participation methods. …”
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Lightweight Encryption Technique to Enhance Medical Image Security on Internet of Medical Things Applications by Mohammad Kamrul Hasan, Shayla Islam, Rossilawati Sulaiman, Sheroz Khan, Aisha-Hassan Abdalla Hashim, Shabana Habib, Mohammad Islam, Saleh Alyahya, Musse Mohamed Ahmed, Samar Kamil, Md Arif Hassan

“…Therefore, patients may lose the privacy of data contents since images are different from the text because of their two particular factors of loss of data and confidentiality. …”
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Digital assistants for education and support of patients with endocrine disorders by Milić Marko Kimi, Sinanović Šćepan, Prodović Tanja, Subotić Slobodan, Kilibarda Tatjana

“…However, challenges such as data privacy concerns, trust in technology, and acce-ssibility issues remain barriers to broader adoption. …”
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Iman di Era Digital: Praktik Konseling Pastoral Berbasis Teknologi Digital by Andreas Fredriko Simatupang, Gunawan Yuli Agung Suprabowo

“…However, there are also shortcomings such as a lack of mastery of digital technology among companions, data privacy and security issues, formal legitimacy from church authorities, as well as a potential reduction in the depth of interpersonal relationships. …”
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Enhancing heart disease classification with M2MASC and CNN-BiLSTM integration for improved accuracy by Vivek Pandey, Umesh Kumar Lilhore, Ranjan Walia, Roobaea Alroobaea, Majed Alsafyani, Abdullah M. Baqasah, Sultan Algarni

“…Blockchain integration ensures stored health data’s security, transparency, and immutability, addresses privacy concerns, and promotes trust in the predictive system. …”
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Implementing community-based interventions for the management of chronic conditions in low- and middle-income countries: A scoping review of qualitative evidence. by Syreen Hassan, Nancy Kagwanja, Brahima Diallo, Robinson Oyando, Pablo Perel, Anthony Etyang, Benjamin Tsofa, Ellen Nolte, IHCoR-Africa Collaborators

“…Eligible studies were those with a qualitative design that explored implementation challenges and facilitators of community-based interventions. Data were thematically analysed and interpreted using the Socio-Ecological Model (SEM) to capture multi-level influences on implementation. …”
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HELA-CMM: capability maturity model for adoption of learning analytics in higher education by Diana Šimić, Nina Begičević Ređep, Sabina Rako, Nikola Kadoić, Wim Van Petegem, Bart Rienties, Nati Cabrera Lanzo, Michael Eichhorn, Lourdes Guàrdia, Sandra Kučina Softić, Alexander Tillmann

“…The proposed maturity model comprises 28 capabilities grouped into eight categories: (1) Teaching / Learning / Assessment, (2) Data Management and Analytics, (3) Ethics, Privacy, Legal Issues, (4) People Competences, (5) Management / Leadership, (6) Culture, (7) Infrastructure, and (8) Quality Assurance. …”
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A Deep Learning-Based Ensemble Framework for Robust Android Malware Detection by Sainag Nethala, Pronoy Chopra, Khaja Kamaluddin, Shahid Alam, Soltan Alharbi, Mohammad Alsaffar

“…The exponential growth of Android applications has resulted in a surge of malware threats, posing severe risks to user privacy and data security. To address these challenges, this study introduces a novel malware detection approach utilizing an ensemble of Convolutional Neural Networks (CNNs) for enhanced classification accuracy. …”
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Towards trustworthy AI-driven leukemia diagnosis: A hybrid Hierarchical Federated Learning and explainable AI framework by Khadija Pervez, Syed Irfan Sohail, Faiza Parwez, Muhammad Abdullah Zia

“…Hierarchical federated learning reduced communication costs by 15% while maintaining data privacy. The integration of explainable artificial intelligence improved the transparency of model decisions, with a high area under the ROC curve (AUC) of 0.98 for the classification of leukemia cells. …”
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Challenges and Lessons Learned in Managing Web-Based Survey Fraud for the Garnering Effective Outreach and Research in Georgia for Impact Alliance–Community Engagement Alliance Sur... by Leslie S Craig, Christina L Evans, Brittany D Taylor, Jace Patterson, Kaleb Whitfield, Mekhi Hill, Michelle Nwagwu, Mohamed Mubasher, Robert A Bednarczyk, Gail G McCray, Cheryl L R Gaddis, Natasha Taylor, Emily Thompson, Ursula Douglas, Saundra K Latimer, Sedessie G Spivey, Tabia Henry Akintobi, Rakale Collins Quarells

“… Abstract BackgroundConvenience, privacy, and cost-effectiveness associated with web-based data collection have facilitated the recent expansion of web-based survey research. …”
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Attitude and Practice towards Pre-exposure Prophylaxis (PrEP) for HIV Prevention among Female Sex Workers in Kicukiro District, Rwanda by Alice Umulisa, Dr Yves Urayeneza, Viateur Hategekimana

“…Primary data was collected using a structured questionnaire, at 10 health centers. …”
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Research Progress in Artificial Intelligence for Central Serous Chorioretinopathy: A Systematic Review by Ping Zhang, Qing Zhang, Xinya Hu, Wei Chi, Weihua Yang

“…Incorporating federated learning for privacy-preserving data sharing and prioritizing explainability will be essential to overcoming barriers to physician adoption and improving trust in AI-driven clinical decision-making. …”
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Diagnostic Applications of AI in Sports: A Comprehensive Review of Injury Risk Prediction Methods by Carmina Liana Musat, Claudiu Mereuta, Aurel Nechita, Dana Tutunaru, Andreea Elena Voipan, Daniel Voipan, Elena Mereuta, Tudor Vladimir Gurau, Gabriela Gurău, Luiza Camelia Nechita

“…This review also addresses critical issues such as data quality, ethical concerns, privacy, and the need for transparency in AI applications. …”
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Reinforcement learning based route optimization model to enhance energy efficiency in internet of vehicles by Quadeer Hussain, Ahmad Shukri Mohd Noor, Muhammad Mukhtar Qureshi, Jianqiang Li, Atta-ur Rahman, Aghiad Bakry, Tariq Mahmood, Amjad Rehman

“…However, some issues remain, like data protection, privacy, compatibility with other protocols and systems, and the availability of stable and continuous connections. …”
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Exploring mHealth app utilization for diabetes self-management: survey insights from a northern district in Malaysia by Premaa Supramaniam, Ying-Shan Beh, Suria Junus, Philip Rajan Devesahayam

“…Users perceived the mHealth app as useful (97.5%), yet faced challenges over the app initiation, charges and data security. …”
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