Personalized Mobile Health for Elderly Home Care: A Systematic Review of Benefits and Challenges by Shahrbanoo Pahlevanynejad, Sharareh R. Niakan Kalhori, Meysam Rahmani Katigari, Rahil Hosseini Eshpala

“…The results indicated that 25% of the challenges were related to privacy, cybersecurity, and data ownership (10%), technology (7.5%), and implementation (7.5%). …”
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Dispute Resolution in Islamic Economic Transactions: The Role and Function of Sharia Arbitration by Gunawan Widjaja

“…This study examines the function and role of Sharia-based arbitration, focusing on its alignment with the values of justice, efficiency, and confidentiality within Islamic law. Using a literature-based methodology, the research analyzes secondary data from legal sources and previous studies on Sharia arbitration in Indonesia, particularly the practices of the Sharia Arbitration Body (BASYARNAS-MUI). …”
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The Role of Artificial Intelligence in Personalized Medicine: A Computer Science Perspective by Raul Mihai RADULESCU

“… This abstract investigates the role of AI in personalized medicine using a computer science lens that connects the underlying theories with their actual applications. …”
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Artificial Intelligence in Religious Education: Ethical, Pedagogical, and Theological Perspectives by Christos Papakostas

“…Amid increasing digital transformation in education, theological institutions are exploring AI tools for teaching, assessment, and pastoral engagement. Using a critical literature review and analysis of institutional case studies, the paper examines the historical development of AI in education, current applications in general and theological contexts, and the ethical challenges it introduces, especially regarding decision making, data privacy, and bias as well as didactically grounded opportunities such as AI-mediated dialogic simulations. …”
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Reinventing Cybersecurity Internships During the COVID-19 Pandemic by Lori L. Sussman

“…The goal is to reach out to underrepresented populations who may use Federal Work-Study (FWS) or grant sponsored internships to participate. …”
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Generalization challenges in video deepfake detection: methods, obstacles, and technological advances by LI Junjie, WANG Jianzong, ZHANG Xulong, QU Xiaoyang

“…However, its widespread use and decreasing costs pose serious threats to personal privacy and social trust. …”
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Towards responsible artificial intelligence in education: a systematic review on identifying and mitigating ethical risks by Haotian Zhu, Yao Sun, Junfeng Yang

“…In the technology dimension, risks include privacy invasion, data leakage, algorithmic bias, the black box algorithm, and algorithmic error. …”
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Artificial intelligence and machine learning in production efficiency enhancement and sustainable development: a comprehensive bibliometric review by Aristidis Bitzenis, Nikos Koutsoupias, Marios Nosios

“…Despite the promising advancements, the review identifies gaps in ethical considerations, especially in data privacy and labor market implications, and suggests avenues for future research, including the implementation of AI and ML in developing economies and Small and Medium Enterprises (SMEs).…”
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Benchmarking Federated Few-Shot Learning for Video-Based Action Recognition by Nguyen Anh Tu, Nartay Aikyn, Nursultan Makhanov, Assanali Abu, Kok-Seng Wong, Min-Ho Lee

“…This learning approach is particularly useful but challenging due to the limited availability of labeled video data in practice. …”
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Knowledge and Views of Patients With Cardiovascular Disease Toward Pharmacogenomics in The United Arab Emirates by Maram O. Abbas, Azhar T. Rahma, Iffat Elbarazi, Bassam R. Ali, George P. Patrinos, Farah Nagy, Alya Osman, Reem K. Alneyadi, Anwar S. Alshamsi, Mohamed Alraqabani, Zeina Al‐Mahayri, Fatma Al‐Maskari

“…Participants were invited via phone calls or in‐person contact at clinics. Data analysis was conducted using SPSS V.29, incorporating descriptive statistics and multivariable logistic regression. …”
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Enhancing IoT Security in Vehicles: A Comprehensive Review of AI-Driven Solutions for Cyber-Threat Detection by Rafael Abreu, Emanuel Simão, Carlos Serôdio, Frederico Branco, António Valente

“…Despite all the advances, challenges still remain in terms of data privacy and the scalability of AI solutions in IoT security. …”
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A scoping review of the governance of federated learning in healthcare by Rebekah Eden, Ignatius Chukwudi, Chris Bain, Sebastiano Barbieri, Leonie Callaway, Susan de Jersey, Yasmeen George, Alain-Dominique Gorse, Michael Lawley, Peter Marendy, Steven M. McPhail, Anthony Nguyen, Mahnaz Samadbeik, Clair Sullivan

“…Abstract In healthcare, federated learning (FL) is emerging as a methodology to enable the analysis of large and disparate datasets while allowing custodians to retain sovereignty. While FL minimises data-sharing challenges, concerns surrounding ethics, privacy, maleficent use, and harm remain. …”
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A comprehensive analysis of model poisoning attacks in federated learning for autonomous vehicles: A benchmark study by Suzan Almutairi, Ahmed Barnawi

“…Due to the increase in data regulations amid rising privacy concerns, the machine learning (ML) community has proposed a novel distributed training paradigm called federated learning (FL). …”
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Congruent Learning for Self-Regulated Federated Learning in 6G by Jalil Taghia, Farnaz Moradi, Hannes Larsson, Xiaoyu Lan, Adam Orucu, Masoumeh Ebrahimi, Andreas Johnsson

“…Across four networking use cases on several tasks, reflecting different profiles of data heterogeneity and limited availability of data, it is shown that CFL greatly reduces overfitting and in nearly all cases improves the performance—a relative gain of about 21% averaged across all use cases.…”
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Robust hierarchical federated learning with dual-layer filtering mechanism by Chaoyi Yang, Wei Liang, Yuxiang Chen, Jiahong Xiao, Dacheng He, Tianxiong Liu, Jin Wang, Amr Tolba

“…Hierarchical federated learning (HFL) is an effective “cloud-edge-device” distributed model training framework that protects data privacy. During HFL training, poisoning attacks on local data and transmitted models can affect the accuracy of the global model. …”
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Distributed Ledger Technology Based Integrated Healthcare Solution for Bangladesh by Md. Ariful Islam, Md. Antonin Islam, Md. Amzad Hossain Jacky, Md. Al-Amin, Md. Saef Ullah Miah, Md. Muhidul Islam Khan, Md. Iqbal Hossain

“…The proposed solution employs Hyperledger Fabric and Blockchain to ensure data integrity, privacy, permissions, and service availability. …”
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Factors influencing academic staff satisfaction and continuous usage of generative artificial intelligence (GenAI) in higher education by Maria Ijaz Baig, Elaheh Yadegaridehkordi

“…The social influence did not correlate positively with the use of GenAI. Security and privacy were positively associated with staff satisfaction. …”
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Echoes From the Void: Detecting DNS Tunneling With Blackhole Features in Encrypted Scenarios With High Accuracy by Wafa S. Alorainy

“…Experiments were conducted using the GraphTunnel data set (2,975,353 records) and the CIC-Bell-DNS-EXF-2021 (1,019,318 records). …”
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Assessing the transferability of BERT to patient safety: classifying multiple types of incident reports by Ying Wang, Farah Magrabi

“…For ambiguous medium and low severity levels, the F-score improvements ranged from 3.6% to 19.7% across all test datasets.Discussion Fine-tuned BERT led to improved performance, particularly in identifying rare classes and generalising effectively to unseen data, compared with small CNNs.Conclusion Fine-tuned BERT may be useful for classification tasks in patient safety where data privacy, scarcity and imbalance are common challenges.…”
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Predicting and Preventing School Dropout with Business Intelligence: Insights from a Systematic Review by Diana-Margarita Córdova-Esparza, Juan Terven, Julio-Alejandro Romero-González, Karen-Edith Córdova-Esparza, Rocio-Edith López-Martínez, Teresa García-Ramírez, Ricardo Chaparro-Sánchez

“…We collected literature from the Google Scholar and Scopus databases using a comprehensive search strategy, incorporating keywords such as “business intelligence”, “machine learning”, and “big data”. …”
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