Personal profile
Academic Biography
I am currently a lecturer in Computer Science at the School of Computing, Engineering and Digital Technologies at Teesside University. I hold PhD in Intelligent Sensing and Communication from Engineering school at Newcastle University, the UK. Thesis Title: ‘Prognosis Prediction in Retina Vien Occlusion’ using several machine learning and deep learning techniques. MSc degree with distinction in Computer science from Northumbria University, the UK. BSc in Computer Science with First Honour Class from Benghazi University, Benghazi, Libya. My research interests lie in artificial intelligence, focusing on machine learning and deep learning techniques. I have worked closely with designs based on feature extraction of medical images, image processing techniques, and machine learning and deep learning techniques. Teaching experience in several models related to computer science, such as machine learning and programming languages such as python, C and C++.
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Collaborations and top research areas from the last five years
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An Effective Fusion Feature Extraction Method and Random Forest for Predicting Anti-Vegf Treatment Demand for RVO Patients
Elkazza, S. & Lawgaly, A., 11 Sept 2024, ICMLT '24: Proceedings of the 2024 9th International Conference on Machine Learning Technologies. ACM, p. 115-120 6 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open AccessFile37 Downloads (Pure) -
Random Forest model matches clinician performance in forecasting visual outcomes from anti-VEGF treatment in retinal vein occlusion.
Elkazza, S. A. A., George, G., Hogg, J. & Dlay, S., 1 Jun 2021, In: Investigative Ophthalmology and Visual Science. 62, 8, 3192.Research output: Contribution to journal › Meeting Abstract › peer-review
Open Access -
Comment on: Ranibizumab and aflibercept intravitreal injection for treatment naïve and refractory macular oedema in branch retinal vein occlusion.
Elkazza, S., Hogg, J., Simplicio, S. D. & Dlay, S. S., 24 Jul 2020, In: European Journal of Ophthalmology. 32, 1, p. NP303 - NP304 2 p.Research output: Contribution to journal › Letter › peer-review
Open AccessFile13 Downloads (Pure) -
Machine learning techniques increase the accuracy of visual outcome prediction in retinal vein occlusion complicated by macular oedema
Elkazza, S., Hogg, J., Simplicio, S. D. & Dlay, S. S., 1 Jul 2020, p. 36. 1 p.Research output: Contribution to conference › Abstract › peer-review