Domain Name System over HTTPS, privacy and security, DoH traffic, deep learning, correlation, coefficient, privacy, accuracy,f iltering, neural networks, feature extraction, HTTP, real-time systems, Domain Name System, cryptography, deep learning, DNS-over-HTTPS, detection and classification

Zeng, Dake, Dawood, Muhammad, Tu, Shanshan, Al-Antary, Mohammad, Waqas, Muhammad ORCID: https://orcid.org/0000-0003-0814-7544 and Namoun, Abdallah (2025) SmartDoH: A deep learning solution for secure and efficient DNS-over-HTTPS traffic analysis. In: 2025 3rd International Conference on Big Data and Privacy Computing (BDPC). IEEE Xplore . Institute of Electrical and Electronics Engineers (IEEE), Fuzhou, China, pp. 35-40. ISBN 979-8331522926; 979-8331522933 (doi:10.1109/BDPC63545.2025.11135907)

anti-VEGF; artificial intelligence; deep learning; diabetic retinopathy; macular edema

Alryalat, Saif Aldeen, Al-Antary, Mohammad, Arafa, Yasmine, Azad, Babak, Boldyreff, Cornelia ORCID: https://orcid.org/0000-0002-2737-7671, Ghnaimat, Tasneem, Al-Antary, Nada, Alfegi, Safa, Elfalah, Mutasem and Abu-Ameerh, Mohammed (2022) Deep learning prediction of response to anti-vegf among diabetic macular edema patients: Treatment response analyzer system (tras). Diagnostics, 12 (2):312. pp. 1-15. ISSN 2075-4418 (Online) (doi:10.3390/diagnostics12020312)

diabetic retinopathy; image classification; artificial intelligence; multi-scale; convolutional neural network (CNN); attention mechanism

Al-Antary, Mohammad and Arafa, Yasmine (2021) Multi-scale attention network for diabetic retinopathy classification. IEEE Access, 9. pp. 54190-54200. ISSN 2169-3536 (Online) (doi:10.1109/ACCESS.2021.3070685)