Edge Computing Oriented Certificateless Sorting Ciphertext Retrieval Scheme by DUAN Jie, GU Wei, ZHANG Shujuan, GONG Xin

“…[Purposes] In order to ensure the privacy and retrievability of cloud data, ciphertext retrieval technology has emerged. …”
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Ethical Challenges in Blood Donation from Viewpoint of Blood Transfusion Policymakers, Experts and Stakeholders: A Qualitative Study by forouzan akrami, Abolfazl Asghari, tooran mohammadi, abbas sedaghat

“…Purposeful sampling and focus group discussion were used to collect data. Data analysis was performed by Graneheim and Lundman inductive content analysis. …”
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Factors influencing the perceived usability of line pay: An extended technology acceptance model approach by Yogi Tri Prasetyo, Krisna Chandra Susanto, Ko-Hui Chuang, Ruo-Ting Yin, Jia-Wei Chen, Yu-Xuan Zhang, Omar Paolo Benito, Zachariah John A. Belmonte, Maela Madel L. Cahigas, Reny Nadlifatin, Ma. Janice J. Gumasing

“…Utilizing an extended Technology Acceptance Model (TAM), the research integrated additional variables such as social influence, trust, security, and environmental concerns, offering a comprehensive framework to understand user adoption dynamics. 120 Taiwanese participants were surveyed by employing the Purposive Sampling Method and data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). …”
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Based on model randomization and adaptive defense for federated learning schemes by Gaofeng Yue, Xiaowei Han

“…Abstract Federated Learning (FL) is a privacy-enhancing technique that enables multiple participants to collaboratively train machine learning models without sharing their local data. …”
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Analyzing the concept of solitude with the spatial syntax technique in the spatial organization of rural homes; case Study: Bushehr province by Farshid Mesbah, Behzad Vasigh, Mostafa Masoudinezhad

“…In the next stage, graph analysis technique was used to extract data from the drawn maps using tools such as connectivity, relationship, step depth, metric depth, and angle of view with the help of Depth Map software for sample analysis. …”
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Self-monitoring of health - user viewpoints on gathering data using consumer health technologies during leisure time by Nora Weinberger, Martina F. Baumann, Maria Maia

“…It focuses on attitudes toward health data collection, data sharing, privacy concerns, and the use of EEG-supported devices.ResultsFindings reveal a complex landscape of trust and concern. …”
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A data management system for precision medicine. by John J L Jacobs, Inés Beekers, Inge Verkouter, Levi B Richards, Alexandra Vegelien, Lizan D Bloemsma, Vera A M C Bongaerts, Jacqueline Cloos, Frederik Erkens, Patrycja Gradowska, Simon Hort, Michael Hudecek, Manel Juan, Anke H Maitland-van der Zee, Sergio Navarro-Velázquez, Lok Lam Ngai, Qasim A Rafiq, Carmen Sanges, Jesse Tettero, Hendrikus J A van Os, Rimke C Vos, Yolanda de Wit, Steven van Dijk

“…In the AIDPATH project, LogiqCare is used to process patient data, while LogiqScience is used for pseudonymous CAR-T cell production for cancer treatment. …”
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Medical data sharing and synthetic clinical data generation – maximizing biomedical resource utilization and minimizing participant re-identification risks by Simeone Marino, Ruth Cassidy, Joseph Nanni, Yuxuan Wang, Yipeng Liu, Mingyi Tang, Yuan Yuan, Toby Chen, Anik Sinha, Balaji Pandian, Ivo D. Dinov, Michael L. Burns

“…This article introduces an end-to-end, titratable pipeline that generates privacy-preserving “digital twin” datasets from complex EHR and wearable-device records (Apple Watch data from 3029 participants) using DataSifter and Synthetic Data Vault (SDV) methods. …”
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Using big data analytics to improve HIV medical care utilisation in South Carolina: A study protocol by Mohammad Rifat Haider, Bankole Olatosi, Jiajia Zhang, Sharon Weissman, Jianjun Hu, Xiaoming Li

“…The RFA is authorised to collect and merge data from these different sources and to ensure the privacy of all PLWH. …”
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Cybersecurity and Liability in a Big Data World by Maria Lillà Montagnani, Mirta Antonella Cavallo

“…We conclude by showing that, despite this articulate framework, big data and cloud service providers still leverage on their strong market power to use “contractual shields” and escape liability. …”
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Enhanced Blockchain-based Key Generation using Butterfly Optimization Algorithm for Efficient Data Sharing in Cloud Computing by P. Anbumani, R. Dhanapal

“…Secondly, the user's privacy may be adequately protected with a secure authentication paradigm that employs ABS to safeguard the user's private data. …”
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Data Protection in Pre-Tertiary Schools In Ghana by Ephrem Kwaa-Aidoo, Elizabeth Serwaa Baah

“…The study also identifies a lack of coordination, formal guidance, inadequate consent procedures, and fragmented implementation strategies in data protection practices. Furthermore, the use of varied data protection mechanisms by different schools suggests a lack of standardised security protocols, which is likely to result in security gaps. …”
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Personalized federated learning for predicting disability progression in multiple sclerosis using real-world routine clinical data by Ashkan Pirmani, Edward De Brouwer, Ádám Arany, Martijn Oldenhof, Antoine Passemiers, Axel Faes, Tomas Kalincik, Serkan Ozakbas, Riadh Gouider, Barbara Willekens, Dana Horakova, Eva Kubala Havrdova, Francesco Patti, Alexandre Prat, Alessandra Lugaresi, Valentina Tomassini, Pierre Grammond, Elisabetta Cartechini, Izanne Roos, Cavit Boz, Raed Alroughani, Maria Pia Amato, Katherine Buzzard, Jeannette Lechner-Scott, Joana Guimarães, Claudio Solaro, Oliver Gerlach, Aysun Soysal, Jens Kuhle, Jose Luis Sanchez-Menoyo, Daniele Spitaleri, Tunde Csepany, Bart Van Wijmeersch, Radek Ampapa, Julie Prevost, Samia J. Khoury, Vincent Van Pesch, Nevin John, Davide Maimone, Bianca Weinstock-Guttman, Guy Laureys, Pamela McCombe, Yolanda Blanco, Ayse Altintas, Abdullah Al-Asmi, Justin Garber, Anneke Van der Walt, Helmut Butzkueven, Koen de Gans, Csilla Rozsa, Bruce Taylor, Talal Al-Harbi, Attila Sas, Cecilia Rajda, Orla Gray, Danny Decoo, William M. Carroll, Allan G. Kermode, Marzena Fabis-Pedrini, Deborah Mason, Angel Perez-Sempere, Mihaela Simu, Neil Shuey, Bhim Singhal, Marija Cauchi, Todd A. Hardy, Sudarshini Ramanathan, Patrice Lalive, Carmen-Adella Sirbu, Stella Hughes, Tamara Castillo Trivino, Liesbet M. Peeters, Yves Moreau

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Smart Grid IoT Framework for Predicting Energy Consumption Using Federated Learning Homomorphic Encryption by Filip Jerkovic, Nurul I. Sarkar, Jahan Ali

“…Homomorphic Encryption (HE) introduces new dimensions of security and privacy within federated learning (FL) and internet of things (IoT) frameworks that allow preservation of user privacy when handling data for FL occurring in Smart Grid (SG) technologies. …”
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Heterogeneous bioinformatic data encryption on portable devices by Hao Chen, Xiayun Hong, Yao Cheng, Xiaotong Wang, Liyan Chen, Xuan Cheng, Juncong Lin

“…Abstract With the popularity of mobile health monitoring and genome sequencing techniques, the scale of biomedical and genomic data grow rapidly, with their privacy receiving more and more concerns. …”
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Using Large Language Models to Automate Data Extraction From Surgical Pathology Reports: Retrospective Cohort Study by Denise Lee, Akhil Vaid, Kartikeya M Menon, Robert Freeman, David S Matteson, Michael L Marin, Girish N Nadkarni

“…However, the use of LLMs in the health care setting is limited by cost, computing power, and patient privacy concerns. …”
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Blockchain Technology for Secure Patient Data Sharing by Robert-Stefan CIZMAŞ

“… This paper presents a decentralized healthcare data management system that utilizes blockchain technology to address critical challenges in data security, patient privacy, and interoperability of electronic medical records (EMR). …”
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Social media in health care- - Ethically challenging - -Dangerous but attractive- -use with caution by Shrikant B. Mali

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An efficient secure predictive demand forecasting system using Ethereum virtual machine by Himani Saraswat, Mahesh Manchanda, Sanjay Jasola

“…The system leverages the Ethereum virtual machine to establish a secure, decentralized, and tamper‐resistant platform for demand prediction while ensuring data integrity and privacy. By utilizing the capabilities of smart contracts and decentralized applications within the Ethereum ecosystem, the proposed system offers an efficient and transparent solution for demand forecasting challenges. …”
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The Venus score for the assessment of the quality and trustworthiness of biomedical datasets by Davide Chicco, Alessandro Fabris, Giuseppe Jurman

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