![Abdulkerim Duman MSc](https://profiles-cardiff.imgix.net/attachments/4971?w=200&h=200&auto=format&crop=faces&fit=crop&q=90")
Mr Abdulkerim Duman
(he/him)
MSc
Graduate Demonstrator
School of Computer Science and Informatics
- DumanA@cardiff.ac.uk
- Queen's Buildings - North Building, Room N1.51, 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. I am doing my research as a member of Life Imaging and Data Analytics (LIDA) research team.
Publication
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)
Articles
- 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)
Teaching
Demonstrator
CMT309: Computational Data Science 2022-
Research themes
Specialisms
- Biomedical imaging
- Computer vision
- radiomics
- Glioblastoma
- medical image analysis