| Predicting at-risk students at different percentages of course length for early intervention using machine learning models M Adnan, A Habib, J Ashraf, S Mussadiq, AA Raza, M Abid, M Bashir, ... Ieee Access 9, 7519-7539, 2021 | 206 | 2021 |
| Utilizing grid search cross-validation with adaptive boosting for augmenting performance of machine learning models M Adnan, AAS Alarood, MI Uddin, I ur Rehman PeerJ Computer Science 8, e803, 2022 | 80 | 2022 |
| Early detection of seasonal outbreaks from twitter data using machine learning approaches S Amin, MI Uddin, DH AlSaeed, A Khan, M Adnan Complexity 2021 (1), 5520366, 2021 | 33 | 2021 |
| Earliest possible global and local interpretation of students’ performance in virtual learning environment by leveraging explainable AI M Adnan, MI Uddin, E Khan, FS Alharithi, S Amin, AA Alzahrani IEEE Access 10, 129843-129864, 2022 | 23 | 2022 |
| Cloud-supported machine learning system for context-aware adaptive M-learning M Adnan, A Habib, J Ashraf, S Mussadiq Turkish Journal of Electrical Engineering and Computer Sciences 27 (4), 2798 …, 2019 | 16 | 2019 |
| Persuading students for behavior change by determining their personality type M Adnan, H Mukhtar, M Naveed 2012 15th International Multitopic Conference (INMIC), 439-449, 2012 | 13 | 2012 |
| Improving m-learners’ performance through deep learning techniques by leveraging features weights M Adnan, A Habib, J Ashraf, B Shah, G Ali IEEE Access 8, 131088-131106, 2020 | 10 | 2020 |
| Deep neural network based m-learning model for predicting mobile learners' performance M Adnan, A Habib, J Ashraf, S Mussadiq, A ALI Turkish Journal of Electrical Engineering and Computer Sciences 28 (3), 1422 …, 2020 | 6 | 2020 |
| Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems MI Uddin, WK Mashwani IGI Global, 2024 | 5 | 2024 |
| Modeling the spread of COVID-19 by leveraging machine and deep learning models M Adnan, M Altalhi, AA Alarood, MI Uddin Intell. Autom. Soft Comput 31 (3), 1857-1872, 2022 | 3 | 2022 |
| Scaffolding computer programming languages learning with tailored English vocabulary based on learners' performance states M Adnan, A Habib, J Ashraf, S Mussadiq, A Raza EAI Endorsed Transactions on Scalable Information Systems 8 (30), 2020 | 3 | 2020 |
| Assessing the realization of smart phones learning objects in students’ adaptive learning paths M Adnan, A Habib, H Mukhtar, G Ali International Journal of Engineering Research 6 (4), 201-208, 2017 | 3 | 2017 |
| Memory Load and Performance-based Adaptive Smartphone E-learning Framework for E-commerce Applications in Online Learning A Alzahrani, M Adnan, M Aljohani, AA Alarood, MI Uddin Journal of Internet Technology 23 (6), 1353-1365, 2022 | 2 | 2022 |
| Evaluating smart Web and Mobile Based interactive application (SWAMBA) in improving students' study behavior M Adnan, A Habib, J Ashraf, R Khan 2017 International Multi-topic Conference (INMIC), 1-9, 2017 | 2 | 2017 |
| Interpretable multi-horizon time series forecasting of cryptocurrencies by leverage temporal fusion transformer A Farooq, MI Uddin, M Adnan, AA Alarood, E Alsolami, S Habibullah Heliyon 10 (22), 2024 | | 2024 |
| Comparison of adaptive E-learning mobile and web-based software applications effectiveness M Adnan, H Mukhtar 2014 IEEE 14th International Conference on Advanced Learning Technologies, 67-71, 2014 | | 2014 |
Jawad AshrafUniversity of Leicester, UKAdresse e-mail validée de le.ac.uk