Calibrated optional randomized response techniques for efficient and robust estimation of quantitative sensitive variables by Ahmed Audu, Mojeed Abiodun Yunusa, Maggie Aphane, Maria Lekganyane

“…Numerical applications using both real and simulated data supported the theoretical findings, demonstrating that the C-ORRT models exhibited lower biases, reduced variances, higher relative efficiency, enhanced privacy levels, and a better combined metric of variance and privacy. …”
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Ethical and regulatory challenges in machine learning-based healthcare systems: A review of implementation barriers and future directions by Shehu Mohammed, Neha Malhotra

“…Key issues concern patient data privacy, algorithmic bias, absence of transparency, and ambiguous legal liability. …”
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Considerations for using Artificial Intelligence in Medical Education by Ali Hamidi Madani

“…Dear Editor Today, the traditional context and method of education have changed, marking the beginning of the digital era in education. The use of new technologies, such as virtual reality (VR), augmented reality (AR), simulators, and artificial intelligence (AI), is a key factor in improving the quality of education and learning outcomes. …”
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Synthetic data production for biomedical research by Yun Gyeong Lee, Mi-Sook Kwak, Jeong Eun Kim, Min Sun Kim, Dong Un No, Hee Youl Chai

“…Synthetic data, generated using advanced artificial intelligence (AI) techniques, replicates the statistical properties of real-world datasets while excluding identifiable information. …”
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Determinants of Attitude and Intention to Use Virtual Credit Cards in Indonesia by Budi Hartono, Suci Nasehati Sunaningsih, Mumpuni Wahyudiarti Sitoresmi

“…Data analysis was conducted using path analysis, revealing that all variables significantly influence trust and perceived risk, with t-statistics below 0.05 and 0.01. …”
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Establishing and evaluating trustworthy AI: overview and research challenges by Dominik Kowald, Dominik Kowald, Sebastian Scher, Sebastian Scher, Viktoria Pammer-Schindler, Viktoria Pammer-Schindler, Peter Müllner, Kerstin Waxnegger, Lea Demelius, Lea Demelius, Angela Fessl, Angela Fessl, Maximilian Toller, Inti Gabriel Mendoza Estrada, Ilija Šimić, Vedran Sabol, Andreas Trügler, Andreas Trügler, Andreas Trügler, Eduardo Veas, Eduardo Veas, Roman Kern, Roman Kern, Tomislav Nad, Simone Kopeinik

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Can open source large language models be used for tumor documentation in Germany?—An evaluation on urological doctors’ notes by Stefan Lenz, Arsenij Ustjanzew, Marco Jeray, Meike Ressing, Torsten Panholzer

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The Use of Artificial Intelligence in Medical Diagnostics: Opportunities, Prospects and Risks by Nataliia Sheliemina

“…The AI integration in healthcare can revolutionise the industry by improving patient outcomes, optimising resource allocation, and reducing operational costs. However, the AI use in medicine carries certain risks related to ethics and data privacy, shortcomings in the quality of data for training algorithms, and importance of protecting against cyberthreats. …”
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HoRNS-CNN model: an energy-efficient fully homomorphic residue number system convolutional neural network model for privacy-preserving classification of dyslexia neural-biomarkers by Opeyemi Lateef Usman, Ravie Chandren Muniyandi, Khairuddin Omar, Mazlyfarina Mohamad, Ayoade Akeem Owoade, Morufat Adebola Kareem

“…Although, fully homomorphic encryption (FHE)-based methods have been proposed to maintain data confidentiality and privacy, however, existing FHE deep convolutional neural network (CNN) models still face some issues such as low accuracy, high encryption/decryption latency, energy inefficiency, long feature extraction times, and significant cipher-image expansion. …”
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Ethical aspects of the use of social networks during the employment process by Branislav Sančanin

“…On the other hand, candidates applying for a vacant position have the opportunity to get to know an organization's employers and employees in more detail, and to gather more information that can often be decisive when making the final decision on whether or not to send in a job application. Most employers today use social media during the process of collecting data on job candidates. …”
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Multifaceted Assessment of Responsible Use and Bias in Language Models for Education by Ishrat Ahmed, Wenxing Liu, Rod D. Roscoe, Elizabeth Reilley, Danielle S. McNamara

“…This study proposes a framework for the automatic detection of biases and violations of responsible use using a synthetic question-based dataset mimicking student–chatbot interactions. …”
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An Evaluation on the Potential of Large Language Models for Use in Trauma Triage by Kelvin Le, Jiahang Chen, Deon Mai, Khang Duy Ricky Le

“…Overall, the literature highlights multifaceted applications of LLMs, especially in emergency trauma settings, albeit with clear limitations and ethical considerations, such as artificial hallucinations, biased outputs and data privacy issues. There remains room for more rigorous research into refining the consistency and capabilities of LLMs, ensuring their effective integration in real-world trauma triaging to improve patient outcomes and resource utilisation.…”
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The ICE–Lexis nexus: An argument against use of commercial databases in immigration enforcement by Jessica P. Needle, Alan Rubel

“…The plaintiffs allege that use of Accurint (the product Lexis sells to U.S. …”
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Legal Challenges of Marine Insurance Laws in the Use of Unmanned Ships by Mahsa Bahadoran- Baghbaderani, Masoud Shirani, Reza Soltani

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Neuroethical issues in adopting brain imaging for personalized chronic pain management: Attitudes of people with lived experience of chronic pain by Karen Deborah Davis, Monica de Oliveira, Ariana Besik, Daniel Z. Buchman

“…However, they worried that brain scans could be used to dismiss their pain self-report. Most respondents felt there were policies to protect their brain data, but 40% were concerned about privacy and brain scan use against them by their employers/insurers. …”
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COVID-19 detection using federated machine learning. by Mustafa Abdul Salam, Sanaa Taha, Mohamed Ramadan

“…AI plays an essential role in COVID-19 case classification as we can apply machine learning models on COVID-19 case data to predict infectious cases and recovery rates using chest x-ray. …”
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Integrating Visual Cryptography for Efficient and Secure Image Sharing on Social Networks by Lijing Ren, Denghui Zhang

“…This prevalence poses challenges for secure image forwarding, as it is susceptible to privacy leaks when sharing data. While standard encryption algorithms can safeguard the privacy of textual data, image data entail larger volumes and significant redundancy. …”
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Barriers to contraceptive access and use among youths (15–24 Years) living in informal urban settlements of Kigali, Rwanda: a qualitative study by Emmanuel Okiror Okello, Alexandre Edgard Murinzi, Colyse Nduwimana, Rashidah Nambaziira

“…Abstract Background Contraceptive use among youths below 19 years in Rwanda is still very low, as low as 3.7%, yet their level of sexual activity is high. …”
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Phishing as a form of fraud identity theft in healthcare: Victimization during COVID-19 pandemic by Vilić Vida

“…The positive aspects of this kind of communication are undoubtedly obvious and necessary, but they also created new forms of victimization due to insecure protocols for sending e-mails, inadequate level of privacy protection, insufficient information security, the existence of so-called security holes and the use of the same devices and digital services for professional and private purposes. …”
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A technological and legal investigation into how smart states deploy collective intelligence for security and surveillance purposes by Diana M. POPA

“…The article debates the relation between data protection and public and national security in democratic states and shows how the evolving threat landscape influences both the practice and the legislative process around personal data protection and deployment of emerging technologies and use of collective intelligence for security purposes. …”
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