| A review of associative classification mining F Thabtah The Knowledge Engineering Review 22 (1), 37-65, 2007 | 382 | 2007 |
| Phishing detection based associative classification data mining N Abdelhamid, A Ayesh, F Thabtah Expert Systems with Applications 41 (13), 5948-5959, 2014 | 370 | 2014 |
| MMAC: A new multi-class, multi-label associative classification approach FA Thabtah, P Cowling, Y Peng Fourth IEEE International Conference on Data Mining (ICDM'04), 217-224, 2004 | 343 | 2004 |
| Predicting phishing websites based on self-structuring neural network RM Mohammad, F Thabtah, L McCluskey Neural Computing and Applications 25, 443-458, 2014 | 342 | 2014 |
| Data imbalance in classification: Experimental evaluation F Thabtah, S Hammoud, F Kamalov, A Gonsalves Information Sciences 513, 429-441, 2020 | 328 | 2020 |
| MCAR: multi-class classification based on association rule F Thabtah, P Cowling, Y Peng The 3rd ACS/IEEE International Conference onComputer Systems and
, 2005 | 289 | 2005 |
| A machine learning framework for sport result prediction RP Bunker, F Thabtah Applied computing and informatics 15 (1), 27-33, 2019 | 272 | 2019 |
| Intelligent rule‐based phishing websites classification RM Mohammad, F Thabtah, L McCluskey IET Information Security 8 (3), 153-160, 2014 | 258 | 2014 |
| Intelligent phishing detection system for e-banking using fuzzy data mining M Aburrous, MA Hossain, K Dahal, F Thabtah Expert systems with applications 37 (12), 7913-7921, 2010 | 256 | 2010 |
| An assessment of features related to phishing websites using an automated technique RM Mohammad, F Thabtah, L McCluskey 2012 international conference for internet technology and secured
, 2012 | 250 | 2012 |
| Machine learning in autistic spectrum disorder behavioral research: A review and ways forward F Thabtah Informatics for Health and Social Care 43 (2), 1-20, 2018 | 232 | 2018 |
| Autism spectrum disorder screening: machine learning adaptation and DSM-5 fulfillment F Thabtah Proceedings of the 1st International Conference on Medical and health
, 2017 | 196 | 2017 |
| A new machine learning model based on induction of rules for autism detection F Thabtah, D Peebles Health informatics journal 26 (1), 264-286, 2020 | 182 | 2020 |
| A new computational intelligence approach to detect autistic features for autism screening F Thabtah, F Kamalov, K Rajab International journal of medical informatics 117, 112-124, 2018 | 156 | 2018 |
| Tutorial and Critical Analysis of Phishing Websites Methods R Mohammad, F Thabtah, TL McCluskey Computer Science Review, 2015 | 155 | 2015 |
| Predicting phishing websites using classification mining techniques with experimental case studies M Aburrous, MA Hossain, K Dahal, F Thabtah 2010 seventh international conference on information technology: New
, 2010 | 142 | 2010 |
| An accessible and efficient autism screening method for behavioural data and predictive analyses F Thabtah Health informatics journal 25 (4), 1739-1755, 2019 | 119 | 2019 |
| Naïve Bayesian based on Chi Square to categorize Arabic data F Thabtah, M Eljinini, M Zamzeer, W Hadi Proceedings of the 11th international business information management
, 2009 | 103 | 2009 |
| A recent review of conventional vs. automated cybersecurity anti-phishing techniques I Qabajeh, F Thabtah, F Chiclana Computer Science Review 29, 44-55, 2018 | 101 | 2018 |
| Early autism screening: a comprehensive review F Thabtah, D Peebles International journal of environmental research and public health 16 (18), 3502, 2019 | 100 | 2019 |
