A systematic review of consumers’ and healthcare professionals’ trust in digital healthcare by Soraia de Camargo Catapan, Hannah Sazon, Sophie Zheng, Victor Gallegos-Rejas, Roshni Mendis, Pedro H. R. Santiago, Jaimon T. Kelly

“…Trust in digital healthcare is complex and, from a consumers’ perspective, can influence digital healthcare use, adoption, acceptance, and usefulness. Consumers’ trust can be affected by the degree of human interaction in automated interventions, perceived risks, privacy concerns, data accuracy, digital literacy, quality of the digital healthcare intervention, satisfaction, education, and income. …”
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Multimodal Detection of Agitation in People With Dementia in Clinical Settings: Observational Pilot Study by Abeer Badawi, Somayya Elmoghazy, Samira Choudhury, Sara Elgazzar, Khalid Elgazzar, Amer M Burhan

“…ObjectiveThis study proposes a novel, multimodal system for predicting AA episodes in individuals with severe dementia, integrating wearable sensor data and privacy-preserving video analytics. …”
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Understanding acceptance and resistance toward generative AI technologies: a multi-theoretical framework integrating functional, risk, and sociolegal factors by Priyanka Shrivastava

“…This study explores the factors influencing college students’ acceptance and resistance toward generative AI technologies by integrating three theoretical frameworks: the Technology Acceptance Model (TAM), Protection Motivation Theory (PMT), and Social Exchange Theory (SET). Using data from 407 respondents collected through a structured survey, the study employed Structural Equation Modeling (SEM) to examine how functional factors (perceived usefulness, ease of use, and reliability), risk factors (privacy concerns, data security, and ethical issues), and sociolegal factors (trust in governance and regulatory frameworks) impact user attitudes. …”
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The IoT and AI in Agriculture: The Time Is Now—A Systematic Review of Smart Sensing Technologies by Tymoteusz Miller, Grzegorz Mikiciuk, Irmina Durlik, Małgorzata Mikiciuk, Adrianna Łobodzińska, Marek Śnieg

“…However, this review also identifies critical challenges, including high infrastructure costs, limited interoperability, connectivity constraints in rural areas, and ethical concerns regarding transparency and data privacy. To address these barriers, recent innovations have emphasized the potential of Edge AI for local inference, blockchain systems for decentralized data governance, and autonomous platforms for field-level automation. …”
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Design of mTCN framework for disaster prediction a fusion of massive machine type communications and temporal convolutional networks by M. Umadevi, J. Arun Kumar, S. Vishnu Priyan, C. Vivek

“…The objective is to develop a scalable, secure, and efficient system for real-time disaster prediction using IoT data streams. Lightweight edge-based TCNs enable localized anomaly detection, while federated learning ensures privacy-preserving collaborative model training across edge devices. …”
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Encrypted traffic classification method based on convolutional neural network by Rongna XIE, Zhuhong MA, Zongyu LI, Ye TIAN

“…Aiming at the problems of low accuracy, weak generality, and easy privacy violation of traditional encrypted network traffic classification methods, an encrypted traffic classification method based on convolutional neural network was proposed, which avoided relying on original traffic data and prevented overfitting of specific byte structure of the application.According to the data packet size and arrival time information of network traffic, a method to convert the original traffic into a two-dimensional picture was designed.Each cell in the histogram represented the number of packets with corresponding size that arrive at the corresponding time interval, avoiding reliance on packet payloads and privacy violations.The LeNet-5 convolutional neural network model was optimized to improve the classification accuracy.The inception module was embedded for multi-dimensional feature extraction and feature fusion.And the 1*1 convolution was used to control the feature dimension of the output.Besides, the average pooling layer and the convolutional layer were used to replace the fully connected layer to increase the calculation speed and avoid overfitting.The sliding window method was used in the object detection task, and each network unidirectional flow was divided into equal-sized blocks, ensuring that the blocks in the training set and the blocks in the test set in a single session do not overlap and expanding the dataset samples.The classification experiment results on the ISCX dataset show that for the application traffic classification task, the average accuracy rate reaches more than 95%.The comparative experimental results show that the traditional classification method has a significant decrease in accuracy or even fails when the types of training set and test set are different.However, the accuracy rate of the proposed method still reaches 89.2%, which proves that the method is universally suitable for encrypted traffic and non-encrypted traffic.All experiments are based on imbalanced datasets, and the experimental results may be further improved if balanced processing is performed.…”
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The Impact of Travel Behavior Factors on the Acceptance of Carsharing and Autonomous Vehicles: A Machine Learning Analysis by Jamil Hamadneh, Noura Hamdan

“…A stated preference (SP) survey is conducted to collect data on travel behavior, incorporating key attributes such as trip time, trip cost, waiting and walking time, privacy, cybersecurity, and surveillance concerns. …”
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Security Evaluation of Provably Secure ECC-Based Anonymous Authentication and Key Agreement Scheme for IoT by Kisung Park, Myeonghyun Kim, Youngho Park

“…Thus, robust, efficient authentication and key agreement (AKA) protocols are essential to protect data privacy during exchanges between end devices and servers. …”
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Knowledge and Attitudes Related to Telemedicine among Nursing Staff at the Selected Tertiary Care Hospital, Karnataka, India by Gavi Salimath, Shubham Dayanand Narayankar, Sanjeev Chougule

“…Methodology: The cross-sectional study was conducted among 201 staff nurses. The data were collected using a self-structured questionnaire after thorough review of the literature. …”
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Generative Artificial Intelligence Tools in Medical Research (GAMER): Protocol for a Scoping Review and Development of Reporting Guidelines by Xufei Luo, Yih Chung Tham, Mohammad Daher, Zhaoxiang Bian, Yaolong Chen, Janne Estill

“…However, the increasing use of GenAI tools in medical research presents challenges, including ethical concerns, data privacy issues, and the potential for generating false content. …”
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Impact of e-banking service quality on e-loyalty in pandemic times through interplay of e-satisfaction by Inzamam Ul Haq, Tahir Mumtaz Awan

“…Design/methodology/approach – The data was collected through an adapted questionnaire by using emails and messaging applications. …”
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The role of cognitive computing in NLP by Laura Orynbay, Gulmira Bekmanova, Banu Yergesh, Assel Omarbekova, Ayaulym Sairanbekova, Altynbek Sharipbay

“…Ethical concerns, including biases in AI, data privacy and societal impact, are critical to address for responsible deployment. …”
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Backdoor Attack Against Dataset Distillation in Natural Language Processing by Yuhao Chen, Weida Xu, Sicong Zhang, Yang Xu

“…We introduce malicious triggers into synthetic data during the distillation phase to execute a backdoor attack on downstream models trained with these data. …”
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FedDL: personalized federated deep learning for enhanced detection and classification of diabetic retinopathy by Dasari Bhulakshmi, Dharmendra Singh Rajput

“…Our primary goal is to develop a system that can monitor various medical facilities while ensuring privacy during the training of DL models. This is made possible through federated learning (FL), which allows for the sharing of parameters instead of actual data, employing a decentralized training approach. …”
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Internet of Things in healthcare: An adaptive ethical framework for IoT in digital health by Abubakar Wakili, Sara Bakkali

“…This approach was employed to validate and refine the AEFIDH, ensuring it encapsulates critical ethical dimensions, including data privacy, informed consent, user autonomy, algorithmic fairness, regulatory compliance, ethical design, and equitable access to healthcare services. …”
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From motion to meaning: understanding students’ seating preferences in libraries through PIR-enabled machine learning and explainable AI by Gizem Izmir Tunahan, Goksu Tuysuzoglu, Hector Altamirano

“…This study presents a comprehensive, data-driven investigation into students’ seating preferences within academic library environments, aiming to inform user-centered spatial design. …”
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Secure and Trustworthy Open Radio Access Network (O-RAN) Optimization: A Zero-Trust and Federated Learning Framework for 6G Networks by Mohammed El-Hajj

“…To mitigate these, we design a Zero-Trust Architecture (ZTA) enforcing continuous authentication and micro-segmentation for RIC components, coupled with an FL framework that enables collaborative ML training across operators without exposing raw network data. A differential privacy mechanism is applied to global model updates to prevent inference attacks. …”
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Challenges Faced By Female Counselors in Providing HIV Testing and Counseling Services in Kashmir: A Qualitative Interpretive Inquiry by Mariya Amin Qurieshi, Inaamul Haq, Khalid Bashir, S. Mohammad Salim Khan, Samir Mattoo, Irfan Farooq Bhat, Imran Ahmad Rather

“…One interview with a counselor from Leh was conducted via Zoom. Data were transcribed and analyzed using IPA to identify the key themes. …”
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What are the Thoughts of Women Whose Husbands’ Frozen Testicular Sperm Is Thawed for in vitro Fertilization on the Day of Oocyte Retrieval? A Qualitative Study by He Y, Wei Q, Chen X, Zhang C, Wang Z

“…Semi-structured, in-depth interviews were conducted to gather qualitative data. The Colaizzi 7-step analysis method was subsequently utilized to analyze the interview transcripts and identify emerging themes.Results: The analysis yielded 3 themes: (1) facing challenges and requiring assistance (a. demonstrate a strong desire to acquire professional knowledge; b. demonstrate a strong desire for recognition); (2) overwhelming psychological stress (a. concerns about potential privacy breaches; b. concerns about security issues; c. concerns about the therapeutic efficacy); (3) improving family atmosphere and marital relationships (a. communication between couples has increased.; b. shared expectations for children help couples establish a common goal).Conclusion: It is recommended that healthcare practitioners implement strategies to enhance patient education and awareness surrounding assisted reproductive technology. …”
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ESMART: Energy-Efficient Slice-Mix-Aggregate for Wireless Sensor Network by Chaoran Li, Yun Liu

“…The proposed scheme performs secure data aggregation in a more efficient way while keeping a good performance of privacy preservation. …”
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