How participation in deliberative engagement affects awareness of, and attitudes towards, genomics research and data sharing: evidence from rural Ghana by Irene Honam Tsey, Pamela Emefa Selormey, John Ganle, Patricia Akweongo, Paulina Tindana

“…Using a quasi-experimental one-group pretest-posttest design, 66 participants completed a baseline survey assessing awareness of genomic research and attitudes toward data sharing. …”
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Is Anonymization Through Discretization Reliable? Modeling Latent Probability Distributions for Ordinal Data as a Solution to the Small Sample Size Problem by Stefan Michael Stroka, Christian Heumann

“…The growing interest in data privacy and anonymization presents challenges, as traditional methods such as ordinal discretization often result in information loss by coarsening metric data. …”
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Tanggung Jawab Perusahaan Terhadap Kebocoran Data Pribadi Dari Penggunaan Teknologi Robotic Process Automation (RPA) Menurut Hukum Positif di Indonesia by Yuni Zakira, Busyra Azheri, Anton Rosari

“…This research uses a normative juridical research type. The data used in this research are secondary data consisting of primary legal materials and secondary legal materials. …”
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Healthcare provision for displaced people in transit: Analyses of routinely collected data from INTERSOS clinics at the Ukrainian border with Moldova and Poland by Saleh Aljadeeah, Seyed-Moeen Hosseinalipour, Nataliia Khanyk, Eszter Szocs, Aliki Traianou, Ana Tomas, Chrysanthi Tatsi, Elżbieta Czapka, Alessandro Verona, Tessa van Boekholt, Ion Chesov, Apostolos Veizis

“…Results: This study used routinely collected data from 1756 patients. …”
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FLPneXAINet: Federated deep learning and explainable AI for improved pneumonia prediction utilizing GAN-augmented chest X-ray data. by Shuvo Biswas, Rafid Mostafiz, Mohammad Shorif Uddin, Muhammad Shahin Uddin

“…Additionally, the need to protect patient privacy complicates the sharing of sensitive clinical data. …”
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Harnessing Moderate-Sized Language Models for Reliable Patient Data Deidentification in Emergency Department Records: Algorithm Development, Validation, and Implementation Study by Océane Dorémus, Dylan Russon, Benjamin Contrand, Ariel Guerra-Adames, Marta Avalos-Fernandez, Cédric Gil-Jardiné, Emmanuel Lagarde

“… Abstract BackgroundThe digitization of health care, facilitated by the adoption of electronic health records systems, has revolutionized data-driven medical research and patient care. While this digital transformation offers substantial benefits in health care efficiency and accessibility, it concurrently raises significant concerns over privacy and data security. …”
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Exploring Current Practices and Challenges of HIPAA Compliance in Software Engineering: Scoping Review by Farah Elkourdi, Chenhao Wei, LU Xiao, Zhongyuan YU, Onur Asan

“…Healthcare systems and applications are increasingly used to improve patient care. However, these applications face data security, privacy, and regulatory compliance challenges. …”
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Retrieval Integrity Verification and Multi-System Data Interoperability Mechanism of a Blockchain Oracle for Smart Healthcare with Internet of Things (IoT) Integration by Ziyuan Zhou, Long Chen, Yekang Zhao, Xinyi Yang, Zhaoyang Han, Zheng He

“…The mechanism uses the cuckoo filter technology to effectively reduce the computational complexity and ensures the authenticity and integrity of data transmission and use through data retrieval integrity verification. …”
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Ethical Design of Data-Driven Decision Support Tools for Improving Cancer Care: Embedded Ethics Review of the 4D PICTURE Project by Marieke Bak, Laura Hartman, Charlotte Graafland, Ida J Korfage, Alena Buyx, Maartje Schermer

“…There are myriad ethical issues to consider as the project will create data-driven prognostic models and develop conversation tools using artificial intelligence while including patient perspectives by setting up boards of experiential experts in 8 different countries. …”
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New method for file deduplication in cloud storage by Chao YANG, Qian JI, Si-chun XIONG, Mao-zhen LIU, Jian-feng MA, Qi JIANG, Lin BAI

“…Deduplication is widely used in cloud storage service to save bandwidth and storage resources,however,the security of client deduplication still flaws in an external attack to access a user’s private data.Xu-CDE,a deduplication solution of encrypting data for multi-client was first proposed,which could protect the privacy of data from the external attackers and honest but curious server,with favorable theoretical meaning and representativeness.However,in Xu-CDE,the user ownership authentication credentials were lack of instantaneity protection,which could not resist replay attack.As an improvement to the flaw,the protocol MRN-CDE (MLE based and random number modified client-side deduplication of encrypted data in cloud storage) was proposed,adding random number in order to ensure the instantaneity of the authentication credentials,and using the algorithm of MLE-K_Pto extract key from original file to replace the file itself as an encryption key.As a consequence,the new protocol improved security while significantly reduced the amount of computation.After the safety analysis and the actual tests,results show that based on Xu-CDE,the proposed protocol MRN-CDE has stronger security of ownership,and improves time efficiency.Specially,the new protocol works better on large files in cloud with a certain value.…”
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New method for file deduplication in cloud storage by Chao YANG, Qian JI, Si-chun XIONG, Mao-zhen LIU, Jian-feng MA, Qi JIANG, Lin BAI

“…Deduplication is widely used in cloud storage service to save bandwidth and storage resources,however,the security of client deduplication still flaws in an external attack to access a user’s private data.Xu-CDE,a deduplication solution of encrypting data for multi-client was first proposed,which could protect the privacy of data from the external attackers and honest but curious server,with favorable theoretical meaning and representativeness.However,in Xu-CDE,the user ownership authentication credentials were lack of instantaneity protection,which could not resist replay attack.As an improvement to the flaw,the protocol MRN-CDE (MLE based and random number modified client-side deduplication of encrypted data in cloud storage) was proposed,adding random number in order to ensure the instantaneity of the authentication credentials,and using the algorithm of MLE-K_Pto extract key from original file to replace the file itself as an encryption key.As a consequence,the new protocol improved security while significantly reduced the amount of computation.After the safety analysis and the actual tests,results show that based on Xu-CDE,the proposed protocol MRN-CDE has stronger security of ownership,and improves time efficiency.Specially,the new protocol works better on large files in cloud with a certain value.…”
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FedCVG: a two-stage robust federated learning optimization algorithm by Runze Zhang, Yang Zhang, Yating Zhao, Bin Jia, Wenjuan Lian

“…Abstract Federated learning provides an effective solution to the data privacy issue in distributed machine learning. …”
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Big Data Analytics for Mental Health Education: A New Framework for University-Level Evaluation under Linguistic Confidence Interval Neutrosophic Numbers by Hong Zhu

“…Ten criteria—including accessibility, awareness, analytics integration, and data ethics—are used to evaluate a diverse set of intervention alternatives ranging from AI-based detection systems to immersive VR training. …”
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Characterizing the neighborhood risk environment in multisite clinic-based cohort studies: A practical geocoding and data linkages protocol for protected health information. by Ariann Nassel, Marta G Wilson-Barthes, Chanelle J Howe, Sonia Napravnik, Michael J Mugavero, Deana Agil, Akilah J Dulin

“…<h4>Background</h4>Maintaining patient privacy when geocoding and linking residential address information with neighborhood-level data can create challenges during research. …”
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Automatic Traffic Data Collection under Varying Lighting and Temperature Conditions in Multimodal Environments: Thermal versus Visible Spectrum Video-Based Systems by Ting Fu, Joshua Stipancic, Sohail Zangenehpour, Luis Miranda-Moreno, Nicolas Saunier

“…Vision-based monitoring systems using visible spectrum (regular) video cameras can complement or substitute conventional sensors and provide rich positional and classification data. …”
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A Framework for Full Decentralization in Blockchain Interoperability by Seth Djanie Kotey, Eric Tutu Tchao, Andrew Selasi Agbemenu, Abdul-Rahman Ahmed, Eliel Keelson

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ChatGPT and Artificial Intelligence in Hospital Level Research: Potential, Precautions, and Prospects by Hassaan B. Arshad, Sara A. Butt, Safi U. Khan, Zulqarnain Javed, Khurram Nasir

“…Furthermore, the review discusses the ethical considerations that arise with AI use in health care, including data privacy, AI interpretability, and the risk of AI-induced disparities. …”
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Private information in public spaces: Facial recognition in the times of smart urban governance by Juliana NOVAES

“…Prior work:  In order to accomplish so, this article analyzes this phenomenon from a capitalism surveillance framework perspective, in light of international data protection standards and with a primary focus on the analysis of the processing of citizens' data in the provision of public services Approach: The main approaches used are literature review and case studies. …”
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Developing a data-informed care planning improvement intervention in long-term care in Nova Scotia: protocol for an advisory-led interpretive qualitative study by Andrea Iaboni, Caitlin McArthur, John Hirdes, Olga Theou, Elaine Moody, Steve Iduye, Luke Turcotte, Lori E Weeks, Michael Kalu, Nazanin Nasiri, Parisa Ghanouni, Kathleen Norman, Samuel Searle, Linda Verlinden

“…This study aims to develop a data-informed care planning improvement intervention that uses routinely collected data to guide resident-centred care planning in LTC. …”
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Opportunities, challenges, and interventions for agriculture 4.0 adoption by Shanmugam Vijayakumar, Varunseelan Murugaiyan, S. Ilakkiya, Virender Kumar, Raman Meenakshi Sundaram, Rapolu Mahender Kumar

“…Major obstacles include high initial investment costs, fragmented land holdings, diverse cropping systems, limited farmer awareness, lack of technical skills, inadequate digital literacy, complex AI algorithms, unreliable infrastructure, insufficient high-quality training data, poor internet connectivity, data privacy concerns, and a lack of supportive government policies. …”
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