Acceptability of Guided Symptom Entry and Asynchronous Clinical Communication Software Among Primary Care Staff: Qualitative Study by Riina Raudne, Taavi Tillmann

“…The software was reported to satisfy perceived feature needs for patient verification, privacy and data security, editable plain-language symptom summaries of symptoms, and integration with prewritten response templates (particularly for staff who were nonnative speakers). …”
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Implementing a chatbot to promote hereditary breast & ovarian cancer genetic screening in women’s health: identifying barriers and facilitators to screening adoption by Easton N. Wollney, Shireen Madani Sims, Luisel J. Ricks-Santi, Elizabeth Eddy, Daniel Wiesman, Carla L. Fisher

“…Findings illustrate how each factor functioned as a facilitator and/or barrier in women’s uptake (e.g., technology being trusted for accuracy versus concerns for data privacy and security). Conclusions While chatbots can extend women’s cancer risk screening access, particularly in rural regions and with college-educated women, systems-level (cost) and individual-level factors (perceived risk, misconceptions about repeating genetic testing) should be addressed to promote adoption. …”
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Foreground-Driven Contrastive Learning for Unsupervised Human Keypoint Detection by Shuxian Li, Hui Luo, Zhengwei Miao, Zhixing Wang, Qiliang Bao, Jianlin Zhang

“…Recently, unsupervised human keypoint detection has become prevalent due to concerns about data privacy. Most existing methods are based on a reconstruction process that extracts appearance and pose information from transformed image pairs and spatially aligns them to obtain a reconstructed image for detection. …”
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Sustainable Innovation: Harnessing AI and Living Intelligence to Transform Higher Education by Hesham Mohamed Allam, Benjamin Gyamfi, Ban AlOmar

“…However, while AI has the potential to improve education significantly, it also introduces challenges, such as ethical concerns, data privacy risks, and algorithmic bias. The real challenge is not just about embracing AI’s benefits but ensuring it is used responsibly, fairly, and in a way that aligns with educational values. …”
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Assessment of the attitude and fears of the physicians of Pakistan regarding artificial intelligence: a cross-sectional survey in 2024 by Abdur Rehman Khalid, Farooq Ahmad, Smak Ahmed, Muhammad Ahrar Bin Naeem, Noor ul Ain, Hassan Mehmood, Aasma Sajawal, Muhammad Umar, Aiman Atta, Hassaan Amin, Shahid Mahmood

“…Subject and methods A nation-wide cross-sectional study was conducted using an online questionnaire, based on standardized General Attitude Towards Artificial Intelligence Scale (GAAIS) and self-devised questions, aimed at collecting data about demographic details, attitude and fears of the physicians regarding AI. …”
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B5G Applications and Emerging Services in Smart IoT Environments by Hani Attar, Mohammed Alghanim, Jafar Ababneh, Khosro Rezaee, Ayat Alrosan, Mohanad A. Deif

“…Furthermore, the proposed study examines the techniques employed for data transmission in B5G applications, such as Vehicle-to-Vehicle (V2V), Device-to-Device (D2D), and Machine to Machine (M2M) transmissions. …”
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Exploring quality of life among elderly persons living with HIV in Accra, Ghana. by Marijanatu Abdulai, Philip Teg-Nefaah Tabong, Harriet Affran Bonful, Adolphina Addo-Lartey, Bismark Sarfo

“…The data was analysed thematically using QSR NVivo 11.…”
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Development of a Solar-Powered Edge Processing Perimeter Alert System with AI and LoRa/LoRaWAN Integration for Drone Detection and Enhanced Security by Mateo Mejia-Herrera, Juan Botero-Valencia, José Ortega, Ruber Hernández-García

“…The system is powered by a LiPo battery, which is recharged using solar energy. The perimeter alert system offers numerous advantages, including edge processing for enhanced data privacy and reduced latency, integrating multiple sensors for increased accuracy, and a decentralized approach to improving security. …”
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Lung-AttNet: An Attention Mechanism-Based CNN Architecture for Lung Cancer Detection With Federated Learning by Chamak Saha, Somak Saha, Md. Asadur Rahman, Md. Mahmudul Haque Milu, Hiroki Higa, Mohd Abdur Rashid, Nasim Ahmed

“…Furthermore, to address medical data sensitivity and privacy concerns, the model is deployed in a Federated Learning (FL) framework, where the global model is trained using weights from local models rather than sharing raw data. …”
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Hybrid Transformer-KAN Within Federated Learning Framework: A Novel Machine Learning Approach for Improved Short-Term Weather Forecasting by Shuai Jin, Qiang Li, Sanqiu Liu, Olebogeng Kevin Joel, Xiaohu Ge

“…Furthermore, federated learning is applied to the proposed method to exploit the spatio-temporal dependencies while protecting data privacy. As a result, a novel framework of Federated-Transformer-KAN is proposed to collaboratively forecast weather variables in a distributed manner, without sharing data that is collected by the intelligent sensors equipped at each weather station locally. …”
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Assessment of breastfeeding self-efficacy in nursing mothers following earthquakes: A case study of the Kahramanmaraş earthquakes in Turkey by Sinem Güven Dinmez, Ozen Karaman, Emine Bakir

“…During the study period, all eligible mothers visiting the polyclinic who met the inclusion criteria were evaluated. Data were collected using a "Descriptive Data Form" and the "Breastfeeding Self-Efficacy Short Form Scale." …”
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A cross-sectional study assessing customers’ perception, satisfaction, and attitude toward e-pharmacy services in Saudi Arabia by Ahmed Khaled Bahamdan, Mona Almanasef

“…A self-administered online questionnaire was distributed via social media, and convenience sampling was used to collect data from December 2022 to January 2023. …”
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Smart cities and electrical and electronic waste management: a review of challenges and opportunities by Deividson Sá Fernandes de Souza, Simone Sehnem, Patricia Guarnieri, Thyago Celso Cavalcante Nepomuceno, Fernando Henrique Taques, Lucio Camara e Silva

“…Key challenges include information security, privacy, interoperability, costs and sustainability. …”
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Differentiating atypical parkinsonian syndromes with hyperbolic few-shot contrastive learning by Won June Choi, Jin HwangBo, Quan Anh Duong, Jae-Hyeok Lee, Jin Kyu Gahm

“…However, the models typically require extensively labeled training datasets, which are costly and pose patient privacy risks. To address the issue of limited training datasets, we propose a novel few-shot learning framework for classifying multiple system atrophy parkinsonian (MSA-P) and progressive supranuclear palsy (PSP) within the APS category using fewer data items. …”
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Vision-Based Activity Recognition for Unobtrusive Monitoring of the Elderly in Care Settings by Rahmat Ullah, Ikram Asghar, Saeed Akbar, Gareth Evans, Justus Vermaak, Abdulaziz Alblwi, Amna Bamaqa

“…The system integrates a frame differencing algorithm with adjustable sensitivity parameters and an anomaly detection model tailored to identify deviations from individual behavior patterns without relying on large volumes of labeled data. The system was validated through real-world deployments across multiple care home rooms, demonstrating significant improvements in emergency response times and ensuring resident privacy through anonymized frame differencing views. …”
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A Multi-Criteria Decision-Making Framework for Blockchain Technology Adoption in Smart Healthcare by Deepika Gaur, Shivani Bali, Angappa Gunasekaran, Nitish Joshi, Kuldeep Chaudhary, Vikram Bali

“…Among the three blockchain platforms evaluated, the results indicate that permissioned blockchain technology is the most suitable for the healthcare sector, primarily due to its strengths in regulatory compliance, data privacy, and system integration. The study’s findings would help practitioners identify and choose the best blockchain platform, thus contributing to a transition in the healthcare industry called “Smart Healthcare 5.0”.…”
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Optimized Identity Authentication via Channel State Information for Two-Factor User Verification in Information Systems by Chuangeng Tian, Fanjia Li, Xiaomeng Liu, Juanjuan Li

“…For classification, a kernel support vector machine (SVM) model is trained using a randomized hyperparameter search algorithm. …”
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Inpatient satisfaction with nursing care in a backward region: a cross-sectional study from northwestern China by Xiaoying Wang, Juxia Zhang, Limei Yang, Jiao Dai, Wenjing Shan, Jiancheng Wang

“…Objectives The aim of the study was to examine the level of patient satisfaction with nursing care and identify the factors affecting satisfaction from the inpatient’s perspective in a backward region of China.Design This was a cross-sectional study.Setting The study was conducted at a tertiary hospital located in northwest China.Participants Patients admitted to the ward for at least 48 hours were chosen to participate in the survey.Primary outcome measure The Newcastle Satisfaction with Nursing Care Scale was used. Data were collected from 219 patients.Results The overall inpatient satisfaction with nursing care was 78.15±4.74. …”
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Intrusion Detection Framework for Internet of Things with Rule Induction for Model Explanation by Kayode S. Adewole, Andreas Jacobsson, Paul Davidsson

“…As the proliferation of Internet of Things (IoT) devices grows, challenges in security, privacy, and interoperability become increasingly significant. …”
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A Trusted Batch Authentication Mechanism Based on Tree for Power Internet of Things by Baohua ZHAO, Zhihao WANG, Liandong CHEN, Chunhui REN, Fajiang YU, Qing XU

“…The structure of unbalanced hash tree generates less verification information during device verification and protects privacy. The sparse Merkel tree multiproofs method is used to generate the verification information to implement the batch authentication of devices. …”
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