| AFCM-LSMA: New intelligent model based on Lévy slime mould algorithm and adaptive fuzzy C-means for identification of COVID-19 infection from chest X-ray images | 0 | 0.34 | 2021 |
| Feature selection strategy based on hybrid crow search optimization algorithm integrated with chaos theory and fuzzy c-means algorithm for medical diagnosis problems | 8 | 0.43 | 2020 |
| Intelligent System For Feature Selection Based On Rough Set And Chaotic Binary Grey Wolf Optimisation | 0 | 0.34 | 2020 |
| Multi-target QSAR modelling of chemo-genomic data analysis based on Extreme Learning Machine | 1 | 0.40 | 2020 |
| A New Type of Fuzzy-Rule-Based System With Chaotic Swarm Intelligence for Multiclassification of Pain Perception From fMRI. | 0 | 0.34 | 2020 |
| A novel parameter estimation in dynamic model via fuzzy swarm intelligence and chaos theory for faults in wastewater treatment plant | 1 | 0.35 | 2020 |
| An improved fast fuzzy c-means using crow search optimization algorithm for crop identification in agricultural. | 4 | 0.44 | 2019 |
| An optimized generic cerebral tumor growth modelling framework by coupling biomechanical and diffusive models with treatment effects | 0 | 0.34 | 2019 |
| Adaptive Neuro-Fuzzy Inference System-Based Chaotic Swarm Intelligence Hybrid Model for Recognition of Mild Cognitive Impairment from Resting-State fMRI. | 0 | 0.34 | 2019 |
| CT liver tumor segmentation hybrid approach using neutrosophic sets, fast fuzzy c-means and adaptive watershed algorithm. | 1 | 0.35 | 2019 |
| Intelligent Hybrid Approach for Feature Selection. | 0 | 0.34 | 2019 |
| A robust swarm intelligence-based feature selection model for neuro-fuzzy recognition of mild cognitive impairment from resting-state fMRI. | 1 | 0.35 | 2019 |
| Macroscopic Cerebral Tumor Growth Modeling From Medical Images: A Review. | 2 | 0.37 | 2018 |
| Computational intelligence optimization approach based on particle swarm optimizer and neutrosophic set for abdominal CT liver tumor segmentation. | 5 | 0.44 | 2018 |
| A Hybrid Approach to Diagnosis of Hepatic Tumors in Computed Tomography Images | 5 | 0.46 | 2014 |
| Neutrosophic Sets and Fuzzy C-Means Clustering for Improving CT Liver Image Segmentation. | 9 | 0.47 | 2014 |
| Automatic computer aided segmentation for liver and hepatic lesions using hybrid segmentations techniques. | 4 | 0.53 | 2013 |
| Automatic Segmentation and Classification of Liver Abnormalities Using Fractal Dimension | 0 | 0.34 | 2013 |
| Automatic mammogram segmentation and computer aided diagnoses for breast tissue density according to BIRADS dictionary. | 3 | 0.42 | 2012 |
