Tracking evolving communities in large linked networks J Hopcroft, O Khan, B Kulis, B Selman Proceedings of the National Academy of Sciences 101 (suppl_1), 5249-5253, 2004 | 468 | 2004 |
IoT-based students interaction framework using attention-scoring assessment in eLearning M Farhan, S Jabbar, M Aslam, M Hammoudeh, M Ahmad, S Khalid, ... Future Generation Computer Systems 79, 909-919, 2018 | 111 | 2018 |
Minimal sufficient explanations for factored markov decision processes O Khan, P Poupart, J Black Proceedings of the International Conference on Automated Planning and …, 2009 | 100 | 2009 |
Responsive architecture/performing instruments P Beesley, O Khan Architectural League of New York, 2009 | 78 | 2009 |
Machine learning algorithms for prediction of health-related quality-of-life after surgery for mild degenerative cervical myelopathy O Khan, JH Badhiwala, CD Witiw, JR Wilson, MG Fehlings The Spine Journal 21 (10), 1659-1669, 2021 | 63 | 2021 |
Predictive modeling of outcomes after traumatic and nontraumatic spinal cord injury using machine learning: review of current progress and future directions O Khan, JH Badhiwala, JRF Wilson, F Jiang, AR Martin, MG Fehlings Neurospine 16 (4), 678, 2019 | 53 | 2019 |
Prediction of worse functional status after surgery for degenerative cervical myelopathy: a machine learning approach O Khan, JH Badhiwala, MA Akbar, MG Fehlings Neurosurgery 88 (3), 584-591, 2021 | 40 | 2021 |
Interactive learning for multimedia at large O Khan, BÞ Jónsson, S Rudinac, J Zahálka, H Ragnarsdóttir, ... Advances in Information Retrieval: 42nd European Conference on IR Research …, 2020 | 31 | 2020 |
Machine learning-based cloud computing improved wheat yield simulation in arid regions AMS Kheir, KA Ammar, A Amer, MGM Ali, Z Ding, A Elnashar Computers and Electronics in Agriculture 203, 107457, 2022 | 14 | 2022 |
Automated refinement of Bayes networks' parameters based on test ordering constraints O Khan, P Poupart, J Agosta Advances in Neural Information Processing Systems 24, 2011 | 14 | 2011 |
Compatibility and challenges in machine learning approach for structural crack assessment K Omar, M Khan, A Starr Structural Health Monitoring 21 (5), 2481-2502, 2022 | 13 | 2022 |
OpenClinical. net: Artificial intelligence and knowledge engineering at the point of care J Fox, M South, O Khan, C Kennedy, P Ashby, J Bechtel BMJ Health & Care Informatics 27 (2), 2020 | 11 | 2020 |
Declarative resilience: A holistic soft-error resilient multicore architecture that trades off program accuracy for efficiency H Omar, Q Shi, M Ahmad, H Dogan, O Khan ACM Transactions on Embedded Computing Systems (TECS) 17 (4), 1-27, 2018 | 11 | 2018 |
Performance analysis of fast Fourier transform on field programmable gate arrays and graphic cards M Ibrahim, O Khan 2016 International Conference on Computing, Electronic and Electrical …, 2016 | 11 | 2016 |
Improved spectral clustering using three-way decisions S Khan, O Khan, N Azam, I Ullah Information Sciences 641, 119113, 2023 | 9 | 2023 |
Exploring tree-based machine learning methods to predict autism spectrum disorder KS Omar, MN Islam, NS Khan Neural Engineering Techniques for Autism Spectrum Disorder, 165-183, 2021 | 8 | 2021 |
Suitability analysis of machine learning algorithms for crack growth prediction based on dynamic response data K Omar, M Khan, A Starr Sensors 23 (3), 1074, 2023 | 7 | 2023 |
Comparative Analysis of Machine Learning Models for Predicting Crack Propagation under Coupled Load and Temperature K Omar, M Khan, A Starr Applied Sciences 13 (12), 7212, 2023 | 5 | 2023 |
Computation of demagnetization tensors by utilizing Fourier properties O Khan, C Ragusa, F Khan IEEE Transactions on Magnetics 50 (11), 1-4, 2014 | 5 | 2014 |
Review of parallel and distributed architectures for micromagnetic codes O Khan, F Khan, C Ragusa, B Montrucchio COMPEL: The International Journal for Computation and Mathematics in …, 2013 | 4 | 2013 |