Abdulkerim Duman
Research student,
- dumana@cardiff.ac.uk
- N1.51, Queen's Buildings - North Building, 5 The Parade, Newport Road, Cardiff, CF24 3AA
Overview
After graduation with biomedical engineering in Turkey, I started an MSc programme in biomedical engineering with bioelectronic stream at Newcastle University. I worked in a start-up company in Istanbul/Turkey after graduating with the MSc degree with distinction. I have used Python and MATLAB during my master and work for signal processing and computer vision/image processing.
I am a postgraduate researcher in the School of Engineering at Cardiff University at the moment. My PhD project is linked with glioblastoma, deep learning, radiomics and federated learning. I am doing my research as a member of Life Imaging and Data Analytics (LIDA) research team.
Publications
2024
- Duman, A., Sun, X., Thomas, S., Powell, J. R. and Spezi, E. 2024. Reproducible and interpretable machine learning-based radiomic analysis for overall survival prediction in glioblastoma multiforme. Cancers 16(19), article number: 3351. (10.3390/cancers16193351)
- Duman, A., Powell, J., Thomas, S., Sun, X. and Spezi, E. 2024. Generalizability of deep learning models on brain tumour segmentation. Presented at: Cardiff University Engineering Research Conference 2023, Cardiff, UK, 12-14 July 2023 Presented at Spezi, E. and Bray, M. eds.Proceedings of the Cardiff University Engineering Research Conference 2023. Cardiff: Cardiff University Press pp. 3-5., (10.18573/conf1.b)
- Doherty, C., Duman, A., Chuter, R., Hutton, M. and Spezi, E. 2024. Investigating the feasibility of MRI auto-segmentation for Image Guided Brachytherapy. Presented at: Cardiff University Engineering Research Conference 2023, Cardiff, UK, 12-14 July 2023 Presented at Spezi, E. and Bray, M. eds.Proceedings of the Cardiff University Engineering Research Conference 2023. Cardiff: Cardiff University Press pp. 11-14., (10.18573/conf1.d)
- Duman, A., Powell, J., Thomas, S. and Spezi, E. 2024. Evaluation of radiomic analysis over the comparison of machine learning approach and radiomic risk score on glioblastoma. Presented at: Cardiff University Engineering Research Conference 2023, Cardiff, UK, 12-14 July 2023 Presented at Spezi, E. and Bray, M. eds.Proceedings of the Cardiff University Engineering Research Conference 2023. Cardiff: Cardiff University Press pp. 19-22., (10.18573/conf1.f)
2023
- Mehmetbeyoglu Duman, E., Duman, A., Taheri, S., Ozkul, Y. and Rassaulzadegan, M. 2023. From data to insights: machine learning empowers prognostic biomarker prediction in Autism. Journal of Personalized Medicine 13(12), article number: 1713. (10.3390/jpm13121713)
- Duman, A., Karakuş, O., Sun, X., Thomas, S., Powell, J. and Spezi, E. 2023. RFS+: A clinically adaptable and computationally efficient strategy for enhanced brain tumor segmentation. Cancers 15(23), article number: 5620. (10.3390/cancers15235620)
- Duman, A., Whybra, P., Powell, J., Thomas, S., Sun, X. and Spezi, E. 2023. PO-1620 Transferability of deep learning models to the segmentation of gross tumour volume in brain cancer. Radiotherapy & Oncology 182(S1), pp. S1315-S1316. (10.1016/S0167-8140(23)66535-1)