SortAlign: a score-based aggregation technique for neural networks in one-round federated learning by Antonio Nappa, Oihan Joyot, Izar Azpiroz, Juan Luis Ferrando Chacón, Mikel Sáez de Buruaga

“…In recent years, the growth of data generated on a daily basis in critical domains, such as industrial processes, where data privacy plays a key role, has led to the strong development of Federated Learning. …”
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Machine Learning in E-Commerce: Trends, Applications, and Future Challenges by Elias Dritsas, Maria Trigka

“…Key challenges related to scalability, interpretability, cold-start problems, data sparsity, and privacy are critically analyzed. …”
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The Process for the Formulation of the International Telehealth Position Statement for Occupational Therapy by Karen Jacobs, Jana Cason, Ann McCullough

“…In 2014, WFOT published the WFOT Telehealth Position Statement on the use of telehealth in occupational therapy. The process for the formulation of the official document involved reviewing WFOT member organizations’ telehealth position statements and data collected from a survey sent to member organizations’ delegates in April 2014.  …”
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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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Large Language Models in Medicine: Clinical Applications, Technical Challenges, and Ethical Considerations by Kyu-Hwan Jung

“…Ethical concerns involve algorithmic bias risking health inequities, threats to patient safety from inaccuracies, unclear accountability, data privacy, and impacts on clinician-patient interactions. …”
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Evaluating the Ethical Practices in Developing AI and Ml Systems in Tanzania by Lazaro Inon Kumbo, Victor Simon Nkwera, Rodrick Frank Mero

“…Artificial Intelligence (AI) and Machine Learning (ML) present transformative opportunities for sectors in developing countries like Tanzania that were previously hindered by manual processes and data inefficiencies. Despite these advancements, the ethical challenges of bias, fairness, transparency, privacy, and accountability are critical during AI and ML system design and deployment. …”
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Implications of Public Disclosure of Personal Information in a Mobile Alert App for People Living With Dementia Who Go Missing: Qualitative Descriptive Study by Adebusola Adekoya, Christine Daum, Noelannah Neubauer, Antonio Miguel-Cruz, Lili Liu

“…NVivo (version 12) was used to manage data, and conventional content analysis was conducted to identify key themes of the implications of public disclosure of personal information in Community ASAP. …”
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User experience with pregnancy tracker mobile apps: Findings from comment-based qualitative study. by Md Alamgir Hossain, Janet Perkins, Md Tanvir Hasan, Sharon Low Bee Lian, Ribica Chowdhury, Md Tanzirul Alam, Anisuddin Ahmed, Mohammad Sohel Shomik, Shams El Arifeen, Ahmed Ehsanur Rahman, Aniqa Tasnim Hossain, M Shafiqur Rahman

“…This study aimed to explore the user experience (UX) of pregnancy tracker mobile apps used by pregnant women.<h4>Methods</h4>This study explored the dynamics between users' experiences and multifaceted dimensions of advanced features, high-quality materials and information, strict privacy policies, problem-solving abilities, and the usefulness of app features and contents. …”
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A hybrid encryption framework leveraging quantum and classical cryptography for secure transmission of medical images in IoT-based telemedicine networks by Arslan Shafique, Syed Ali Atif Naqvi, Ali Raza, Masoud Ghalaii, Panagiotis Papanastasiou, Julie McCann, Qammer H. Abbasi, Muhammad Ali Imran

“…In this context, ensuring secure transmission and communication is necessary to protect medical data to maintain privacy. To address such privacy concerns and secure medical images against cyberattacks, this research presents a robust hybrid encryption framework that integrates quantum, and classical cryptographic methods. …”
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Joint Class and Domain Continual Learning for Decentralized Federated Processes by Chiara Lanza, Tinne Tuytelaars, Marco Miozzo, Eduard Angelats, Paolo Dini

“…So far, learning in IoT scenarios has almost exclusively been studied in a centralized fashion, but CL can be used in decentralized settings involving a multitude of nodes to learn, adapt, and generalize from their streams of data, even with limited communication and computation capabilities. …”
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Federated Reinforcement Learning-Based Dynamic Resource Allocation and Task Scheduling in Edge for IoT Applications by Saroj Mali, Feng Zeng, Deepak Adhikari, Inam Ullah, Mahmoud Ahmad Al-Khasawneh, Osama Alfarraj, Fahad Alblehai

“…The system’s design includes collecting data, fusing and preparing it for use, training models, and performing simulations with EdgeSimPy. …”
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AI’s role in transforming learning environments: a review of collaborative approaches and innovations by Dwi Mariyono, Akmal Nur Alif Hd

“…By automating administrative tasks, AI allows educators to focus on fostering creativity and critical thinking. Ethical AI use: Institutions must establish ethical guidelines to prevent biases in algorithms and protect students’ data privacy, ensuring AI is a tool for equity rather than division. …”
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AI-driven biomarker discovery: enhancing precision in cancer diagnosis and prognosis by Esther Ugo Alum

“…Existing gaps include data quality, algorithmic transparency, and ethical concerns around privacy, among others. …”
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Geodesign in the era of artificial intelligence by Xinyue Ye, Tianchen Huang, Yang Song, Xin Li, Galen Newman, Zhongjie Lin, Dayong Jason Wu

“…AI enhances existing Geodesign methods by automating spatial data analysis, improving land use classification, refining heat island effect assessment, optimizing energy use, facilitating green infrastructure planning, and generating design scenarios. …”
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Blockchain and Its Application in the Peer Review of Scientific Works: A Systematic Review by Cristian Hugo Morales-Alarcón, Elba Bodero-Poveda, Henry Mauricio Villa-Yánez, Pamela Alexandra Buñay-Guisñan

“…However, studies addressing this topic focus on its potential to improve transparency and trust in the process, offer incentives and rewards to reviewers and authors, enhance the quality and fairness of evaluations, and strengthen the security and privacy of the data involved.…”
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kMoL: an open-source machine and federated learning library for drug discovery by Romeo Cozac, Haris Hasic, Jun Jin Choong, Vincent Richard, Loic Beheshti, Cyrille Froehlich, Takuto Koyama, Shigeyuki Matsumoto, Ryosuke Kojima, Hiroaki Iwata, Aki Hasegawa, Takao Otsuka, Yasushi Okuno

“…Graph Convolutional Network (GCN) models have proven especially promising due to their inherent ability to model molecular structures using graph-based representations. However, maximizing the potential of such models in practice is challenging, as companies prioritize data privacy and security over collaboration initiatives to improve model performance and robustness. kMoL is an open-source machine learning library with integrated federated learning capabilities developed to address such challenges. …”
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Telemedicine and information technology in health care management: Perspectives and barriers among the nursing students by N Sheeliya White, S Sathya Franklin, N Juliet, Selvia Arokiya Mary Amalanathan, Puvaneswari Kanagaraj, Anasani Somasekhara Babu

“…Data collection was facilitated through a structured questionnaire, and the gathered data were analyzed using SPSS version 22. …”
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An Intelligent Client Selection Algorithm of Federated Learning for Class-imbalance by ZHU Suxia, WANG Yunmeng, YAN Peisen, SUN Guanglu

“…This algorithm does not use any auxiliary data set. Under the premise of ensuring the privacy of the client ′ s local data invisible to the server it uses the Tanimoto coefficient to measure the difference between the local data distribution and the target distribution. …”
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Artificial intelligence in early warning systems for infectious disease surveillance: a systematic review by Ismael Villanueva-Miranda, Guanghua Xiao, Guanghua Xiao, Yang Xie, Yang Xie

“…After screening 600 records and removing duplicates and non-relevant articles, the search yielded 67 relevant studies for review.ResultsKey findings reveal the prevalent use of machine learning (ML), deep learning (DL), and natural language processing (NLP), which often integrate diverse data sources (e.g., epidemiological, web, climate, wastewater). …”
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A Non-Invasive Approach for Facial Action Unit Extraction and Its Application in Pain Detection by Mondher Bouazizi, Kevin Feghoul, Shengze Wang, Yue Yin, Tomoaki Ohtsuki

“…A significant challenge that hinders advancements in medical research is the sensitive and confidential nature of patient data in available datasets. In particular, sharing patients’ facial images poses considerable privacy risks, especially with the rise of generative artificial intelligence (AI), which could misuse such data if accessed by unauthorized parties. …”
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