Survey of utilisation of fuzzy technology in medicine and healthcare MF Abbod, DG von Keyserlingk, DA Linkens, M Mahfouf Fuzzy Sets and Systems 120 (2), 331-349, 2001 | 334 | 2001 |
Classifiers consensus system approach for credit scoring M Ala'raj, MF Abbod Knowledge-Based Systems 104, 89-105, 2016 | 290 | 2016 |
A survey of fuzzy logic monitoring and control utilisation in medicine M Mahfouf, MF Abbod, DA Linkens Artificial intelligence in medicine 21 (1-3), 27-42, 2001 | 233 | 2001 |
Promoter hypermethylation identifies progression risk in bladder cancer DR Yates, I Rehman, MF Abbod, M Meuth, SS Cross, DA Linkens, ... Clinical Cancer Research 13 (7), 2046-2053, 2007 | 232 | 2007 |
A novel maximum power point tracking technique based on fuzzy logic for photovoltaic systems SD Al-Majidi, MF Abbod, HS Al-Raweshidy International Journal of Hydrogen Energy 43 (31), 14158-14171, 2018 | 219 | 2018 |
A new hybrid ensemble credit scoring model based on classifiers consensus system approach M Ala'raj, MF Abbod Expert systems with applications 64, 36-55, 2016 | 199 | 2016 |
Pain and stress detection using wearable sensors and devices—A review J Chen, M Abbod, JS Shieh Sensors 21 (4), 1030, 2021 | 185 | 2021 |
ECG arrhythmia classification by using a recurrence plot and convolutional neural network BM Mathunjwa, YT Lin, CH Lin, MF Abbod, JS Shieh Biomedical Signal Processing and Control 64, 102262, 2021 | 175 | 2021 |
Artificial immune systems-models, algorithms and applications JR Al-Enezi, MF Abbod, S Alsharhan Academic Research Publishing Agency, 2010 | 160 | 2010 |
Multiresolution analysis using wavelet, ridgelet, and curvelet transforms for medical image segmentation S AlZubi, N Islam, M Abbod International journal of biomedical imaging 2011 (1), 136034, 2011 | 158 | 2011 |
Application of artificial intelligence to the management of urological cancer MF Abbod, JWF Catto, DA Linkens, FC Hamdy The Journal of urology 178 (4), 1150-1156, 2007 | 157 | 2007 |
Artificial intelligence in predicting bladder cancer outcome: a comparison of neuro-fuzzy modeling and artificial neural networks JWF Catto, DA Linkens, MF Abbod, M Chen, JL Burton, KM Feeley, ... Clinical Cancer Research 9 (11), 4172-4177, 2003 | 157 | 2003 |
Defect detection in printed circuit boards using you-only-look-once convolutional neural networks VA Adibhatla, HC Chih, CC Hsu, J Cheng, MF Abbod, JS Shieh Electronics 9 (9), 1547, 2020 | 147 | 2020 |
The impact of the quality of financial reporting on non-financial business performance and the role of organizations demographic'attributes (type, size and experience) AH Al-Dmour, M Abbod, NS Al-Balqa | 143 | 2018 |
Fuzzy logic-based anti-sway control design for overhead cranes M Mahfouf, CH Kee, MF Abbod, DA Linkens Neural Computing & Applications 9, 38-43, 2000 | 131 | 2000 |
A particle swarm optimisation-trained feedforward neural network for predicting the maximum power point of a photovoltaic array SD Al-Majidi, MF Abbod, HS Al-Raweshidy Engineering Applications of Artificial Intelligence 92, 103688, 2020 | 97 | 2020 |
Optimization the initial weights of artificial neural networks via genetic algorithm applied to hip bone fracture prediction YT Chang, J Lin, JS Shieh, MF Abbod Advances in Fuzzy Systems 2012 (1), 951247, 2012 | 84 | 2012 |
Application of multivariate empirical mode decomposition and sample entropy in EEG signals via artificial neural networks for interpreting depth of anesthesia JR Huang, SZ Fan, MF Abbod, KK Jen, JF Wu, JS Shieh Entropy 15 (9), 3325-3339, 2013 | 83 | 2013 |
Applying deep learning to defect detection in printed circuit boards via a newest model of you-only-look-once VA Adibhatla, HC Chih, CC Hsu, J Cheng, MF Abbod, JS Shieh American Institute of Mathematical Sciences (AIMS), 2021 | 82 | 2021 |
Sample entropy analysis for the estimating depth of anaesthesia through human EEG signal at different levels of unconsciousness during surgeries Q Liu, L Ma, SZ Fan, MF Abbod, JS Shieh PeerJ 6, e4817, 2018 | 82 | 2018 |