| TOM: Twitter opinion mining framework using hybrid classification scheme FH Khan, S Bashir, U Qamar Decision support systems 57, 245-257, 2014 | 423 | 2014 |
| Improving heart disease prediction using feature selection approaches S Bashir, ZS Khan, FH Khan, A Anjum, K Bashir 2019 16th international bhurban conference on applied sciences and …, 2019 | 216 | 2019 |
| IntelliHealth: a medical decision support application using a novel weighted multi-layer classifier ensemble framework S Bashir, U Qamar, FH Khan Journal of biomedical informatics 59, 185-200, 2016 | 166 | 2016 |
| A semi-supervised approach to sentiment analysis using revised sentiment strength based on SentiWordNet FH Khan, U Qamar, S Bashir Knowledge and information Systems 51, 851-872, 2017 | 131 | 2017 |
| SentiMI: Introducing point-wise mutual information with SentiWordNet to improve sentiment polarity detection FH Khan, U Qamar, S Bashir Applied Soft Computing 39, 140-153, 2016 | 128 | 2016 |
| An evaluation of machine learning classifiers and ensembles for early stage prediction of lung cancer MI Faisal, S Bashir, ZS Khan, FH Khan 2018 3rd international conference on emerging trends in engineering …, 2018 | 115 | 2018 |
| HMV: A medical decision support framework using multi-layer classifiers for disease prediction S Bashir, U Qamar, FH Khan, L Naseem Journal of Computational Science 13, 10-25, 2016 | 105 | 2016 |
| An ensemble based decision support framework for intelligent heart disease diagnosis S Bashir, U Qamar, MY Javed International conference on information society (i-Society 2014), 259-264, 2014 | 99 | 2014 |
| eSAP: A decision support framework for enhanced sentiment analysis and polarity classification FH Khan, U Qamar, S Bashir Information Sciences 367, 862-873, 2016 | 89 | 2016 |
| BagMOOV: A novel ensemble for heart disease prediction bootstrap aggregation with multi-objective optimized voting S Bashir, U Qamar, FH Khan Australasian physical & engineering sciences in medicine 38, 305-323, 2015 | 88 | 2015 |
| An efficient rule-based classification of Diabetes using ID3, C4. 5, & CART ensembles S Bashir, U Qamar, FH Khan, MY Javed 2014 12th International Conference on Frontiers of Information Technology …, 2014 | 84 | 2014 |
| Heterogeneous classifiers fusion for dynamic breast cancer diagnosis using weighted vote based ensemble S Bashir, U Qamar, FH Khan Quality & Quantity 49, 2061-2076, 2015 | 83 | 2015 |
| SWIMS: Semi-supervised subjective feature weighting and intelligent model selection for sentiment analysis FH Khan, U Qamar, S Bashir Knowledge-based systems 100, 97-111, 2016 | 72 | 2016 |
| MV5: a clinical decision support framework for heart disease prediction using majority vote based classifier ensemble S Bashir, U Qamar, FH Khan, MY Javed Arabian Journal for Science and Engineering 39, 7771-7783, 2014 | 61 | 2014 |
| Churn prediction using neural network based individual and ensemble models M Saghir, Z Bibi, S Bashir, FH Khan 2019 16th International Bhurban Conference on Applied Sciences and …, 2019 | 43 | 2019 |
| QoS based dynamic web services composition & execution FH Khan, S Bashir, MY Javed, A Khan, MSH Khiyal arXiv preprint arXiv:1003.1502, 2010 | 42 | 2010 |
| A multicriteria weighted vote‐based classifier ensemble for heart disease prediction S Bashir, U Qamar, FH Khan Computational Intelligence 32 (4), 615-645, 2016 | 41 | 2016 |
| Lexicon based semantic detection of sentiments using expected likelihood estimate smoothed odds ratio FH Khan, U Qamar, S Bashir Artificial Intelligence Review 48, 113-138, 2017 | 36 | 2017 |
| A knowledge-based clinical decision support system utilizing an intelligent ensemble voting scheme for improved cardiovascular disease prediction S Bashir, AA Almazroi, S Ashfaq, AA Almazroi, FH Khan IEEE Access 9, 130805-130822, 2021 | 33 | 2021 |
| An ensemble based approach using a combination of clustering and classification algorithms to enhance customer churn prediction in telecom industry SF Bilal, AA Almazroi, S Bashir, FH Khan, AA Almazroi PeerJ Computer Science 8, e854, 2022 | 31 | 2022 |
Dr. Farhan Hassan KhanCollege of Electrical & Mechanical Engineering, National University of Sciences & Technology (NUST)在 ceme.nust.edu.pk 的电子邮件经过验证
