The Impact of Artificial Intelligence (AI) on Students’ Academic Development by Aniella Mihaela Vieriu, Gabriel Petrea

“…However, challenges such as over-reliance on AI, diminished critical thinking skills, data privacy risks, and academic dishonesty were also identified. …”
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Application progress of artificial intelligence in managing thyroid disease by Qing Lu, Yu Wu, Jing Chang, Li Zhang, Qing Lv, Hui Sun

“…Despite the broad prospects of AI applications, challenges related to data privacy, model interpretability, and clinical applicability remain. …”
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An efficient ECC and fuzzy verifier based user authentication protocol for IoT enabled WSNs by T. Sudhakar, R. Praveen, V. Natarajan

“…Ensuring integrity and privacy of data while transmitting it from sensors to the data analytics servers is crucial in open network. …”
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Mapping the landscape of machine learning in chronic disease management: A comprehensive bibliometric study by Shiying Shen, Wenhao Qi, Sixie Li, Jianwen Zeng, Xin Liu, Xiaohong Zhu, Chaoqun Dong, Bin Wang, Qian Xu, Shihua Cao

“…Conclusion ML is rapidly integrating into personalized medicine, real-time monitoring, and multimodal data fusion. However, challenges such as limited collaboration, weak model generalization, and data privacy persist. …”
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Efficient Elliptic-Curve-Cryptography-Based Anonymous Authentication for Internet of Things: Tailored Protocols for Periodic and Remote Control Traffic Patterns by Shunfang Hu, Yuanyuan Zhang, Yanru Guo, Yanru Chen, Liangyin Chen

“…IoT-based applications require effective anonymous authentication and key agreement (AKA) protocols to secure data and protect user privacy due to open communication channels and sensitive data. …”
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Machine learning for post-diploma educational and career guidance: a scoping review in AI-driven decision support systems by Flavio Manganello, Elisa Rasca, Alberto Villa, Andrea Maddalena, Giannangelo Boccuzzi

“…This scoping review maps the application of ML in post-diploma guidance by examining the types of models used, data sources, reported outcomes, and ethical considerations related to fairness, privacy, and transparency. …”
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The Application of Artificial Intelligence in Medical Diagnostics: Implications for Sports Medicine by Michał Bolek, Dominika Musialska, Aleksandra Kędzia, Bartosz Jagieła, Monika Fidyk, Magda Minkiewicz, Maciej Dyda

“…However, their integration into healthcare raises critical ethical concerns related to data privacy, algorithmic bias, and transparency. …”
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FedDyH: A Multi-Policy with GA Optimization Framework for Dynamic Heterogeneous Federated Learning by Xuhua Zhao, Yongming Zheng, Jiaxiang Wan, Yehong Li, Donglin Zhu, Zhenyu Xu, Huijuan Lu

“…Federated learning (FL) is a distributed learning technique that ensures data privacy and has shown significant potential in cross-institutional image analysis. …”
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Trusted execution environments for quantum computers by Theodoros Trochatos, Chuanqi Xu, Sanjay Deshpande, Yao Lu, Yongshan Ding, Jakub Szefer, Jakub Szefer

“…The cloud-based environments in which today's and future quantum computers will operate raise concerns about the security and privacy of user's intellectual property, whether code, or data, or both. …”
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Integrating artificial intelligence in drug discovery and early drug development: a transformative approach by Alberto Ocana, Atanasio Pandiella, Cristian Privat, Iván Bravo, Miguel Luengo-Oroz, Eitan Amir, Balazs Gyorffy

“…Ethical and regulatory issues, such as data privacy, also challenge the implementation of AI. …”
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Advancing Pediatric Growth Assessment with Machine Learning: Overcoming Challenges in Early Diagnosis and Monitoring by Mauro Rodriguez-Marin, Luis Gustavo Orozco-Alatorre

“…Unlike complex machine learning models, it offers parsimony in transparency, efficiency, and reproducibility, making it ideal for clinical settings where explainable, data-driven decisions are essential. Methods: A logistic regression model was developed using R to analyze biometric and demographic data from a cross-sectional dataset, including real-world data from public institucions. …”
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Federated Online Learning for adaptive load forecasting across decentralized nodes by Mohamed Ahmed T.A. Elgalhud, Mohammad Navid Fekri, Syed Mir, Katarina Grolinger

“…The main drawbacks are twofold: (1) data sharing and transfer results in privacy and security risks, and (2) static models miss opportunities to learn from new data. …”
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Cross-Receiver Radio Frequency Fingerprint Identification: A Source-Free Adaptation Approach by Jian Yang, Shaoxian Zhu, Zhongyi Wen, Qiang Li

“…We propose a novel approach called contrastive source-free cross-receiver network (CSCNet), which employs contrastive learning to facilitate model adaptation using only unlabeled data from the deployed receiver. …”
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Advances in Infant Cry Paralinguistic Classification—Methods, Implementation, and Applications: Systematic Review by Geofrey Owino, Bernard Shibwabo

“…ConclusionsThe evolution of infant cry classification methods has progressed from traditional classical statistical methods to machine learning models but with minimal considerations of data privacy, confidentiality, and ultimate deployment to practical use. …”
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Gathering requirements for IoT-assisted wellbeing in elementary school—a multi-stakeholder perspective by Karin Brodén, Jonas Andersson, Agnieszka Kitkowska, Awais Ahmad, Peter Mozelius

“…We analyzed the data in an inductively and deductively way, using the Konu and Rimpelä’s wellbeing framework.ResultsOur novel findings reveal alignment between staff and student perspectives across the framework’s categories: having, loving, being and health. …”
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A Comprehensive Investigation of Anomaly Detection Methods in Deep Learning and Machine Learning: 2019–2023 by Shalini Kumari, Chander Prabha, Asif Karim, Md. Mehedi Hassan, Sami Azam

“…FL provides a collaborative way to improve AD using distributed data sources and data privacy.…”
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The Role of Artificial Intelligence (AI) in Transforming Small and Medium Enterprises (SMEs): by Mugisha, Justin, Francis Adyanga, Akena, Ocan, Johnson

“…Also, it was found that building workforce capacity through collaborations and customized training programs can help close the skills gap, while improving cybersecurity and implementing efficient data management frameworks can help with privacy issues. …”
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Leveraging large language models for the deidentification and temporal normalization of sensitive health information in electronic health records by Hong-Jie Dai, Tatheer Hussain Mir, Ching-Tai Chen, Chien-Chang Chen, Hao-Ping Yang, Chung-Hong Lee, Yi-Yun Chou, Yu-Chin Teng, Shalini Gupta, Omkar Panchal, Divyabharathy Ramesh Nadar, Wei-Hsiang Liao, Yu-Chuan Lin, Zi-Rui Zhao, Richard Tzong-Han Tsai, Yung-Chun Chang, Jitendra Jonnagaddala

“…Abstract Secondary use of electronic health record notes enhances clinical outcomes and personalized medicine, but risks sensitive health information (SHI) exposure. …”
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Influencing Factors and Correlations of User Satisfaction with Mobile Health Applications by SHI Qin, XIE Jing, WU Shang

“…Using the grounded theory, the study extracted factors influencing user satisfaction with mobile health applications by coding the review data. …”
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Revolutionizing Sports: The Role of Wearable Technology and AI in Training and Performance Analysis by Stanisław Dudek, Weronika Koziak, Michalina Makieła, Aleksandra Bętkowska, Agata Kornacka, Wojciech Dudek, Kamila Szostak, Rafał Tomaka, Anna Byra

“…Additionally, AI-driven wearables raise concerns over data security, ethical handling, and equitable access, as high costs limit their use in amateur sports. …”
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