| Arteriovenous ratio and papilledema based hybrid decision support system for detection and grading of hypertensive retinopathy S Akbar, MU Akram, M Sharif, A Tariq, U ullah Yasin Computer methods and programs in biomedicine 154, 123-141, 2018 | 92 | 2018 |
| Decision support system for detection of hypertensive retinopathy using arteriovenous ratio S Akbar, MU Akram, M Sharif, A Tariq, SA Khan Artificial intelligence in medicine 90, 15-24, 2018 | 80 | 2018 |
| Decision support system for detection of papilledema through fundus retinal images S Akbar, MU Akram, M Sharif, A Tariq, UU Yasin Journal of medical systems 41, 1-16, 2017 | 70 | 2017 |
| Automated techniques for blood vessels segmentation through fundus retinal images: A review S Akbar, M Sharif, MU Akram, T Saba, T Mahmood, M Kolivand Microscopy research and technique 82 (2), 153-170, 2019 | 58 | 2019 |
| Automated detection of brain tumor through magnetic resonance images using convolutional neural network S Gull, S Akbar, HU Khan BioMed Research International 2021, 2021 | 55 | 2021 |
| Automatic detection of papilledema through fundus retinal images using deep learning T Saba, S Akbar, H Kolivand, S Ali Bahaj Microscopy Research and Technique 84 (12), 3066-3077, 2021 | 53 | 2021 |
| Data on fundus images for vessels segmentation, detection of hypertensive retinopathy, diabetic retinopathy and papilledema MU Akram, S Akbar, T Hassan, SG Khawaja, U Yasin, I Basit Data in brief 29, 105282, 2020 | 50 | 2020 |
| Artificial intelligence in brain tumor detection through MRI scans: advancements and challenges S Gull, S Akbar Artificial Intelligence and Internet of Things, 241-276, 2021 | 48 | 2021 |
| Recent developments in detection of central serous retinopathy through imaging and artificial intelligence techniques–a review SA Hassan, S Akbar, A Rehman, T Saba, H Kolivand, SA Bahaj IEEE Access 9, 168731-168748, 2021 | 41 | 2021 |
| Deep learning-based automatic detection of central serous retinopathy using optical coherence tomographic images SAE Hassan, S Akbar, S Gull, A Rehman, H Alaska 2021 1st International Conference on Artificial Intelligence and Data …, 2021 | 34 | 2021 |
| Artificial intelligence techniques for glaucoma detection through retinal images: State of the art A Shoukat, S Akbar Artificial Intelligence and Internet of Things, 209-240, 2021 | 30 | 2021 |
| AVRDB: annotated dataset for vessel segmentation and calculation of arteriovenous ratio S Akbar, T Hassan, MU Akram, UU Yasin, I Basit 21st International Conference on Image Processing, Computer Vision and …, 2017 | 28 | 2017 |
| Detection of microscopic glaucoma through fundus images using deep transfer learning approach S Akbar, SA Hassan, A Shoukat, J Alyami, SA Bahaj Microscopy Research and Technique, 2022 | 27 | 2022 |
| ullah Yasin, U. Arteriovenous ratio and papilledema based hybrid decision support system for detection and grading of hypertensive retinopathy S Akbar, MU Akram, M Sharif, A Tariq Comput. Methods Programs Biomed 154, 123-141, 2018 | 22 | 2018 |
| Deep learning approach to diagnose Alzheimer’s disease through magnetic resonance images MF Ahmad, S Akbar, SAE Hassan, A Rehman, N Ayesha 2021 International Conference on Innovative Computing (ICIC), 1-6, 2021 | 21 | 2021 |
| An interactive deep learning approach for brain tumor detection through 3D-magnetic resonance images S Gull, S Akbar, K Safdar 2021 International Conference on Frontiers of Information Technology (FIT …, 2021 | 20 | 2021 |
| An automated deep learning based ensemble approach for malignant melanoma detection using dermoscopy images K Safdar, S Akbar, S Gull 2021 International Conference on Frontiers of Information Technology (FIT …, 2021 | 18 | 2021 |
| A deep learning-based automatic method for early detection of the glaucoma using fundus images A Shoukat, S Akbar, K Safdar 2021 International conference on innovative computing (ICIC), 1-6, 2021 | 18 | 2021 |
| Artificial intelligence in coronavirus detection: Recent findings and future perspectives SA Hassan, S Gull, S Akbar, I Hanif, S Iqbal, MW Aziz Intelligent Computing Applications for COVID-19, 23-48, 2021 | 17 | 2021 |
| An automated deep learning approach to diagnose glaucoma using retinal fundus images A Shoukat, S Akbar, SAE Hassan, A Rehman, N Ayesha 2021 international conference on frontiers of information technology (FIT …, 2021 | 16 | 2021 |
Muhammad Usman AkramProfessor & Director BIOMISA Research Group, National University of Sciences & TechnologyGeverifieerd e-mailadres voor ceme.nust.edu.pk
