Data mining in manufacturing: a review JA Harding, M Shahbaz, Srinivas, A Kusiak | 717 | 2006 |
Performance analysis of data mining classification techniques to predict diabetes S Perveen, M Shahbaz, A Guergachi, K Keshavjee Procedia Computer Science 82, 115-121, 2016 | 339 | 2016 |
Manufacturing system engineering ontology for semantic interoperability across extended project teams HK Lin, JA Harding*, M Shahbaz International journal of production research 42 (24), 5099-5118, 2004 | 146 | 2004 |
A systematic machine learning based approach for the diagnosis of non-alcoholic fatty liver disease risk and progression S Perveen, M Shahbaz, K Keshavjee, A Guergachi Scientific reports 8 (1), 2112, 2018 | 105 | 2018 |
Applications of association rule mining in health informatics: a survey W Altaf, M Shahbaz, A Guergachi Artificial Intelligence Review 47, 313-340, 2017 | 93 | 2017 |
Product design and manufacturing process improvement using association rules M Shahbaz, M Srinivas, JA Harding, M Turner Proceedings of the Institution of Mechanical Engineers, Part B: Journal of …, 2006 | 90 | 2006 |
Metabolic syndrome and development of diabetes mellitus: predictive modeling based on machine learning techniques S Perveen, M Shahbaz, K Keshavjee, A Guergachi IEEE Access 7, 1365-1375, 2018 | 83 | 2018 |
Context based positive and negative spatio-temporal association rule mining M Shaheen, M Shahbaz, A Guergachi Knowledge-based systems 37, 261-273, 2013 | 82 | 2013 |
Classification of Alzheimer's Disease using Machine Learning Techniques. M Shahbaz, S Ali, A Guergachi, A Niazi, A Umer Data, 296-303, 2019 | 80 | 2019 |
Negative and positive association rules mining from text using frequent and infrequent itemsets S Mahmood, M Shahbaz, A Guergachi The Scientific World Journal 2014 (1), 973750, 2014 | 65 | 2014 |
Handling irregularly sampled longitudinal data and prognostic modeling of diabetes using machine learning technique S Perveen, M Shahbaz, T Saba, K Keshavjee, A Rehman, A Guergachi IEEE Access 8, 21875-21885, 2020 | 62 | 2020 |
Streamflow forecasting by modeling the rainfall–streamflow relationship using artificial neural networks S Ali, M Shahbaz Modeling Earth Systems and Environment 6 (3), 1645-1656, 2020 | 50 | 2020 |
Influence of foliar-applied triacontanol on growth, gas exchange characteristics, and chlorophyll fluorescence at different growth stages in wheat under saline conditions S Perveen, M Shahbaz, M Ashraf Photosynthetica 51, 541-551, 2013 | 50 | 2013 |
Prognostic modeling and prevention of diabetes using machine learning technique S Perveen, M Shahbaz, K Keshavjee, A Guergachi Scientific reports 9 (1), 13805, 2019 | 47 | 2019 |
Data mining applications in hydrocarbon exploration M Shaheen, M Shahbaz, Z ur Rehman, A Guergachi Artificial Intelligence Review 35, 1-18, 2011 | 45 | 2011 |
Triacontanol-induced changes in growth, yield, leaf water relations, oxidative defense system, minerals, and some key osmoprotectants in Triticum aestivum under saline conditions S Perveen, M Shahbaz, M Ashraf Turkish Journal of Botany 38 (5), 896-913, 2014 | 43 | 2014 |
Classification by object recognition in satellite images by using data mining M Shahbaz, A Guergachi, A Noreen, M Shaheen Proceedings of the world congress on engineering 1, 4-6, 2012 | 38 | 2012 |
Data mining methodology in perspective of manufacturing databases M Shahbaz, SA Masood, M Shaheen, A Khan Journal of American Science 6 (11), 999-1012, 2010 | 38 | 2010 |
A hybrid approach to tea crop yield prediction using simulation models and machine learning D Batool, M Shahbaz, H Shahzad Asif, K Shaukat, TM Alam, IA Hameed, ... Plants 11 (15), 1925, 2022 | 36 | 2022 |
Arasencorpus: A semi-supervised approach for sentiment annotation of a large arabic text corpus A Al-Laith, M Shahbaz, HF Alaskar, A Rehmat Applied Sciences 11 (5), 2434, 2021 | 36 | 2021 |