Objective: Although computer technologies are now widely used in medicine, little is known about its use among medical students in Iran. The aim of this study was to determine the competence and access to computer and internet among the medical students.
Methods: In this descriptive study, medical students of Shahid Sadoughi University of Medical Science, Yazd, Iran from the fifth years were asked to answer a questionnaire during a time-tabled lecture slot. The chi-square test was used to compare the frequency of computer and internet use between the two genders, and the level of statistical significance for all test was set at 0.05.
Results: All the students have a personal computer and internet access. There were no statistically significant differences between men and women for the computer and internet access, use wireless device to access internet, having laptop and e-mail address and the difficulties encountered using internet. The main reason for less utilization of internet was slow speed of data transfer.
Conclusions: Because of the wide range of computer skills and internet information among medical students in our institution, a single computer and internet course for all students would not be useful nor would it be accepted.
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http://dx.doi.org/10.12669/pjms.305.5355 | DOI Listing |
J Med Internet Res
January 2025
Black Dog Institute, University of New South Wales, Sydney, Australia.
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Department of Computing, Glasgow Caledonian University, Glasgow, G4 0BA, Scotland.
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EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, 11586, Riyadh, Saudi Arabia.
During the Covid-19 pandemic, the widespread use of social media platforms has facilitated the dissemination of information, fake news, and propaganda, serving as a vital source of self-reported symptoms related to Covid-19. Existing graph-based models, such as Graph Neural Networks (GNNs), have achieved notable success in Natural Language Processing (NLP). However, utilizing GNN-based models for propaganda detection remains challenging because of the challenges related to mining distinct word interactions and storing nonconsecutive and broad contextual data.
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Department of Electrical Engineering, Indian Institute of Technology Delhi, New Delhi, India.
Online Mental Health Communities (OMHCs), such as Reddit, have witnessed a surge in popularity as go-to platforms for seeking information and support in managing mental health needs. Platforms like Reddit offer immediate interactions with peers, granting users a vital space for seeking mental health assistance. However, the largely unregulated nature of these platforms introduces intricate challenges for both users and society at large.
View Article and Find Full Text PDFPLoS One
January 2025
School of Electrical and Electronic Engineering, Hanoi University of Science and Technology, Hanoi, Vietnam.
The explosion of Internet-of-Thing enables several interconnected devices but also gives rise chance for unauthorized parties to compromise sensitive information through wireless communication systems. Covert communication therefore has emerged as a potential candidate for ensuring data privacy in conjunction with physical layer transmission to render two lines of defense. In this paper, we aim to enhance the individual transmission of nearby users in non-orthogonal multiple access (NOMA) systems under scenarios of an eavesdropper who monitors covert transmission before decoding covert information.
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