Common benchmark functions for metaheuristic evaluation: A review K Hussain, MNM Salleh, S Cheng, R Naseem JOIV: International Journal on Informatics Visualization 1 (4-2), 218-223, 2017 | 134 | 2017 |
A survey on bug prioritization J Uddin, R Ghazali, MM Deris, R Naseem, H Shah Artificial Intelligence Review 47, 145-180, 2017 | 104 | 2017 |
An empirical evaluation of machine learning techniques for chronic kidney disease prophecy B Khan, R Naseem, F Muhammad, G Abbas, S Kim IEEE Access 8, 55012-55022, 2020 | 93 | 2020 |
Software defect prediction for healthcare big data: an empirical evaluation of machine learning techniques B Khan, R Naseem, MA Shah, K Wakil, A Khan, MI Uddin, M Mahmoud Journal of Healthcare Engineering 2021 (1), 8899263, 2021 | 57 | 2021 |
Cooperative Clustering for Software Modularization R Naseem, O Maqbool, S Muhammad Journal of Systems and Software 86 (8), 2045 – 2062, 2013 | 57 | 2013 |
Improved similarity measures for software clustering R Naseem, O Maqbool, S Muhammad 2011 15th European Conference on Software Maintenance and Reengineering, 45-54, 2011 | 52 | 2011 |
Effect of negation in sentiment analysis W Sharif, NA Samsudin, MM Deris, R Naseem 2016 sixth international conference on innovative computing technology …, 2016 | 47 | 2016 |
ABioNER: A BERT‐Based Model for Arabic Biomedical Named‐Entity Recognition N Boudjellal, H Zhang, A Khan, A Ahmad, R Naseem, J Shang, L Dai Complexity 2021 (1), 6633213, 2021 | 43 | 2021 |
Artificial bee colony algorithm: A component-wise analysis using diversity measurement K Hussain, MNM Salleh, S Cheng, Y Shi, R Naseem Journal of King Saud University-Computer and Information Sciences 32 (7 …, 2020 | 37 | 2020 |
A review on data preprocessing methods for class imbalance problem H Ali, MNM Salleh, K Hussain, A Ahmad, A Ullah, A Muhammad, ... International Journal of Engineering & Technology 8 (3), 390-397, 2019 | 34 | 2019 |
Exploration and exploitation measurement in swarm-based metaheuristic algorithms: An empirical analysis MNM Salleh, K Hussain, S Cheng, Y Shi, A Muhammad, G Ullah, ... Recent Advances on Soft Computing and Data Mining: Proceedings of the Third …, 2018 | 31 | 2018 |
Improving CBIR accuracy using convolutional neural network for feature extraction A Shah, R Naseem, S Iqbal, MA Shah 2017 13th International Conference on Emerging Technologies (ICET), 1-5, 2017 | 31 | 2017 |
Performance assessment of classification algorithms on early detection of liver syndrome R Naseem, B Khan, MA Shah, K Wakil, A Khan, W Alosaimi, MI Uddin, ... Journal of Healthcare Engineering 2020 (1), 6680002, 2020 | 30 | 2020 |
A dataset for software requirements risk prediction ZS Shaukat, R Naseem, M Zubair 2018 IEEE International conference on computational science and engineering …, 2018 | 25 | 2018 |
Machine learning approaches for liver disease diagnosing B Khan, R Naseem, M Ali, M Arshad, N Jan International Journal of Data Science and Advanced Analytics 1 (1), 27-31, 2019 | 22 | 2019 |
Fetal heart rate classification and comparative analysis using cardiotocography data and KNOWN classifiers R Afridi, Z Iqbal, M Khan, A Ahmad, R Naseem International Journal of Grid and Distributed Computing (IJGDC) 12, 31-42, 2019 | 22 | 2019 |
An improved similarity measure for binary features in software clustering R Naseem, O Maqbool, S Muhammad 2010 Second International Conference on Computational Intelligence …, 2010 | 22 | 2010 |
Investigating tree family machine learning techniques for a predictive system to unveil software defects R Naseem, B Khan, A Ahmad, A Almogren, S Jabeen, B Hayat, MA Shah Complexity 2020 (1), 6688075, 2020 | 20 | 2020 |
Empirical assessment of machine learning techniques for software requirements risk prediction R Naseem, Z Shaukat, M Irfan, MA Shah, A Ahmad, F Muhammad, ... Electronics 10 (2), 168, 2021 | 19 | 2021 |
Identification of challenges during requirements implementation in global software development: A systematic M Yaseen, R Naseem, Z Ali, G Ullah vol 4, 23-40, 2019 | 19 | 2019 |