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Nusrat Zerin Zenia
Researcher at Jahangirnagar University
Publications - 14
Citations - 437
Nusrat Zerin Zenia is an academic researcher from Jahangirnagar University. The author has contributed to research in topics: Computer science & Health care. The author has an hindex of 7, co-authored 11 publications receiving 237 citations.
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Journal ArticleDOI
Application of deep learning in detecting neurological disorders from magnetic resonance images: a survey on the detection of Alzheimer’s disease, Parkinson’s disease and schizophrenia
TL;DR: The comparative performance analysis of various DL architectures across different disorders and imaging modalities suggests that the Convolutional Neural Network outperforms other methods in detecting neurological disorders.
Book ChapterDOI
Detecting Neurodegenerative Disease from MRI: A Brief Review on a Deep Learning Perspective
TL;DR: The results show that deep learning based techniques can detect the level of disorder with relatively high accuracy and some possible future research directions are provided.
Journal ArticleDOI
Energy-efficiency and reliability in MAC and routing protocols for underwater wireless sensor network
TL;DR: It is found that the protocols for UWSN are highly selective, and the fitness of any protocol depends solely on the application and design requirements, which is addressed by this review.
Book ChapterDOI
6G Access Network for Intelligent Internet of Healthcare Things: Opportunity, Challenges, and Research Directions
M. Shamim Kaiser,Nusrat Zerin Zenia,Fariha Tabassum,Shamim Al Mamun,Arifur Rahman,Md. Shahidul Islam,Mufti Mahmud +6 more
TL;DR: In this article, the authors present the framework of 6G cellular networks, its aggregation with multidimensional communication techniques such as optical wireless communication network, cell-free communication system, backhaul network, and quantum communication, as well as distributed security paradigm in the context of Internet of Healthcare Things (IoHT).
Journal ArticleDOI
i Worksafe: Towards Healthy Workplaces During COVID-19 With an Intelligent Phealth App for Industrial Settings
M. Shamim Kaiser,Mufti Mahmud,Manan Binth Taj Noor,Nusrat Zerin Zenia,Shamim Al Mamun,K. M. Abir Mahmud,Saiful Azad,V. N. Manjunath Aradhya,Punitha Stephan,Thompson Stephan,Ramani Kannan,Mohammed Hanif,Tamanna Sharmeen,Tianhua Chen,Amir Hussain +14 more
TL;DR: In this paper, a mobile app-based intelligent portable healthcare (pHealth) tool, called ${i}$ WorkSafe, is presented to assist industries in detecting possible suspects for COVID-19 infection among their employees who may need primary care.