Overview
Dr Muhammad Azizur Rahman is a Lecturer in Data Science at Cardiff Metropolitan University. He is an experienced IT professional and researcher in wide range of topics related to the broad area of Computing/Data Science and user of programming and database querying languages, statistics, Network Simulator, NS-2/NAM, GLOMOSIM, Computer Networks, Communications Software Engineering, Network Simulation methods and tools, Modelling, Formal Ontologies. Rahman has been working with very large databases of routinely collected data as well as computer communications network. Having worked in Medical and Population Health settings, and computer networking, Rahman has experience in working and teaching across different disciplines and within a very multidisciplinary team.
Research Publications
The pattern of anti-IL-6 versus non-anti-IL-6 biologic disease modifying anti-rheumatic drugs use in patients with rheumatoid arthritis in Wales, UK: a real-world study using electronic health records
Cooksey, R., Kennedy, J., Rahman, M., Brophy, S. & Choy, E., 14 Dec 2024, In: Rheumatology Advances in Practice. 9, 1, p. rkae140 rkae140.Research output: Contribution to journal › Article › peer-review
Receipt of social services intervention in childhood, educational attainment and emergency hospital admissions: longitudinal analyses of national administrative health, social care, and education data in Wales, UK
Lowthian, E., Moore, G., Evans, A., Anthony, R., Rahman, M. A., Daniel, R., Brophy, S., Scourfield, J., Taylor, C., Paranjothy, S. & Long, S., 21 Oct 2024, In: BMC Public Health. 24, 1, p. 2912 1 p., 2912.Research output: Contribution to journal › Article › peer-review
Enhancing Audio Classification Through MFCC Feature Extraction and Data Augmentation with CNN and RNN Models
Rezaul, K. M., Jewel, M., Islam, M. S., Siddiquee, K. N. E. A., Barua, N., Rahman, M. A., Shan-A-Khuda, M., Sulaiman, R. B., Shaikh, M. S. I., Hamim, M. A., Tanmoy, F. M., Haque, A. U., Nipun, M. S., Dorudian, N., Kareem, A., Farid, A. K., Mubarak, A., Jannat, T. & Asha, U. F. T., Jul 2024, In: International Journal of Advanced Computer Science and Applications. 15, 7, p. 37-53 17 p.Research output: Contribution to journal › Article › peer-review
Mental health analysis of international students using machine learning techniques
Rahman, M. A., Kohli, T. & Alemayehu, Y. (Editor), 6 Jun 2024, In: PLoS ONE. 19, 6, p. e0304132 e0304132.Research output: Contribution to journal › Article › peer-review
Predicting a diagnosis of ankylosing spondylitis using primary care health records- A machine learning approach
Kennedy, J., Kennedy, N., Cooksey, R., Choy, E., Siebert, S., Rahman, M. & Brophy, S., 31 Mar 2023, In: PLoS ONE. 18, 3 MARCH, e0279076.Research output: Contribution to journal › Article › peer-review
Tools and Techniques for Teaching and Research in Network Design and Simulation
Rahman, M. A. & Pakstas, A., 17 Mar 2023, In: SN Computer Science. 4, 3, 269.Research output: Contribution to journal › Article › peer-review
Weighting of risk factors for low birth weight: A linked routine data cohort study in Wales, UK
Bandyopadhyay, A., Jones, H., Parker, M., Marchant, E., Evans, J., Todd, C., Rahman, M. A., Healy, J., Win, T. L., Rowe, B., Moore, S., Jones, A. & Brophy, S., 10 Feb 2023, In: BMJ open. 13, 2, e063836.Research output: Contribution to journal › Article › peer-review
Predicting Hospital Readmission for Campylobacteriosis from Electronic Health Records: A Machine Learning and Text Mining Perspective
Zhou, S. M., Lyons, R. A., Rahman, M. A., Holborow, A. & Brophy, S., 10 Jan 2022, In: Journal of Personalized Medicine. 12, 1, p. 86 1 p., 86.Research output: Contribution to journal › Article › peer-review
Timing of parental depression on risk of child depression and poor educational outcomes: A population based routine data cohort study from Born in Wales, UK
Brophy, S., Todd, C., Rahman, M. A., Kennedy, N. & Rice, F., 17 Nov 2021, In: PLoS ONE. 16, 11 November, e0258966.Research output: Contribution to journal › Article › peer-review
Biologic use in psoriatic arthritis and ankylosing spondylitis patients: A descriptive epidemiological study using linked, routine data in Wales, UK
Cooksey, R., Rahman, M. A., Kennedy, J., Brophy, S. & Choy, E., 27 Jun 2021, In: Rheumatology Advances in Practice. 5, 2, rkab042.Research output: Contribution to journal › Article › peer-review