Muhammad Rizwan
| Name | Muhammad Rizwan |
|---|---|
| Job title | Lecturer in Computer Science |
| Research institute | College of Science and Engineering |
| ORCID | https://orcid.org/0000-0002-4408-4934 |
Research outputs
Voice-based early diagnosis of Parkinson’s Disease using spectrogram features and AI models
Quamar, D., Ambeth Kumar, V. D., Rizwan, M., Bagdasar, O. and Kadar, M. 2025. Voice-based early diagnosis of Parkinson’s Disease using spectrogram features and AI models. Bioengineering. 12 (10), pp. 1-29. https://doi.org/10.3390/bioengineering12101052Device-to-device communication in 5G heterogeneous network based on game-theoretic approaches: A comprehensive survey
Ahmad, R. Z., Rizwan, M., Yousuf, M. J., Khan, MB., Almadhor, A., Gadekallu, T. R. and Abbas S. 2025. Device-to-device communication in 5G heterogeneous network based on game-theoretic approaches: A comprehensive survey. Journal of Network and Computer Applications. 238. https://doi.org/10.1016/j.jnca.2025.104152Transferability Evaluation in Wi-Fi Intrusion Detection Systems Through Machine Learning and Deep Learning Approaches
Yonbawi, S., Afzal, A., Yasir, M., Rizwan, M. and Kryvinska, N. 2025. Transferability Evaluation in Wi-Fi Intrusion Detection Systems Through Machine Learning and Deep Learning Approaches. IEEE Access. 13, pp. 11248 - 11264. https://doi.org/10.1109/ACCESS.2025.3528214Deep Learning-Driven Anomaly Detection for IoMT-Based Smart Healthcare Systems
Khan, A., Rizwan, M., Bagdasar, O., Alabdulatif, A., Alamro, S. and Alnajim, A. 2024. Deep Learning-Driven Anomaly Detection for IoMT-Based Smart Healthcare Systems. Computer Modeling in Engineering & Sciences . 141 (3), pp. 2121-2141. https://doi.org/10.32604/cmes.2024.054380Adaptation of Federated Explainable Artificial Intelligence for Efficient and Secure E-Healthcare Systems
Abid, R., Rizwan, M., Alabdulatif, A., Alnajim, A., Alamro, M. and Azrour, M. 2024. Adaptation of Federated Explainable Artificial Intelligence for Efficient and Secure E-Healthcare Systems. CMC-Computers, Materials & Continua. pp. 1-17. https://doi.org/10.32604/cmc.2024.046880Artificial Intelligence for Cognitive Health Assessment: State-of-the-Art, Open Challenges and Future Directions
Javed, A. R., Saadia, A., Mughal, H., Gadekallu, T.R., Rizwan, M., Maddikunta, P.K.R., Mahmud, M., Liyanage, M and Hussain, A. 2023. Artificial Intelligence for Cognitive Health Assessment: State-of-the-Art, Open Challenges and Future Directions. Cognitive Computation. pp. 1-46. https://doi.org/10.1007/s12559-023-10153-4Intrusion Detection Framework for Industrial Internet of Things Using Software Defined Network
Alshahrani, H., Khan, A., Rizwan, M., Al Reshan, M. S., Sulaiman, A. and Shaikh, A. 2023. Intrusion Detection Framework for Industrial Internet of Things Using Software Defined Network. Sustainability. 15 (11), pp. 1-18. https://doi.org/10.3390/su15119001Intelligent Transportation Systems in Smart City: A Systematic Survey
Hassan, M. A., Javed, R., Farhatullah, Granelli, F., Gen, X., Rizwan, M., Ali, S. H., Junaid, H. and Ullah, S. 2023. Intelligent Transportation Systems in Smart City: A Systematic Survey. 2023 International Conference on Robotics and Automation in Industry (ICRAI). IEEE Computer Society. https://doi.org/10.1109/ICRAI57502.2023.10089543Enhanced clustering based routing protocol in vehicular ad‐hocnetworks
Afia, N., Rizwan, M., Shtwai, A., Almadhor, A., Akhtaruzzaman, Md., Islam, S. and Rahman, H. 2023. Enhanced clustering based routing protocol in vehicular ad‐hocnetworks. IET Electrical Systems in Transportation. 13 (1), pp. 1-15. https://doi.org/10.1049/els2.12069Brain Tumor and Glioma Grade Classification Using Gaussian Convolutional Neural Network
Rizwan, M., Aysha, S., Maryam, S., AR Javed, Baker, T. and Dhiya, O. 2022. Brain Tumor and Glioma Grade Classification Using Gaussian Convolutional Neural Network. IEEE Access. 10, pp. 29731 - 29740. https://doi.org/10.1109/ACCESS.2022.3153108Exploratory Data Analysis, Classification, Comparative Analysis, Case Severity Detection, and Internet of Things in COVID 19 Telemonitoring for Smart Hospitals
Shabbir, A., Shabbir, M., Javed, A. R., Rizwan, M., Iwendi, C. and Chakraborty, C. 2022. Exploratory Data Analysis, Classification, Comparative Analysis, Case Severity Detection, and Internet of Things in COVID 19 Telemonitoring for Smart Hospitals. Journal of Experimental & Theoretical Artificial Intelligence. 35 (4), pp. 507-534. https://doi.org/10.1080/0952813X.2021.1960634978
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