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2020 – today
- 2022
[j5]Jale Bektas, Yasin Bektas
, Evrim Ersin Kangal:
Integrating a novel SRCRN network for segmentation with representative batch-mode experiments for detecting melanoma. Biomed. Signal Process. Control. 71(Part): 103218 (2022)- [j4]Jale Bektas, Arwa Elsadig:
A unified workflow strategy for analysing large-scale TripAdvisor reviews with BOW model. Int. J. Bus. Intell. Data Min. 21(1): 102-117 (2022) - [j3]Jale Bektas, Turgay Ibrikci:
Optimisations of four imputation frameworks for performance exploring based on decision tree algorithms in big data analysis problems. Int. J. Comput. Sci. Eng. 25(5): 523-531 (2022) - [j2]Jale Bektas:
EKSL: An effective novel dynamic ensemble model for unbalanced datasets based on LR and SVM hyperplane-distances. Inf. Sci. 597: 182-192 (2022)
2010 – 2019
- 2017
- [b1]Jale Bektas:
Use of data mining techniques to determine presence of coronary artery disease and deriving a risk score by employing risk factors (Veri madenciliği tekniklerinin kullanılarak koroner arter hastalığının varlığının belirlenmesi ve risk faktörlerinin kullanılmasıyla bir risk skor sisteminin oluşturulması). Çukurova University, Turkey, 2017 - [j1]Jale Bektas, Turgay Ibrikci, I. Türkay Özcan:
Classification of Real Imbalanced Cardiovascular Data Using Feature Selection and Sampling Methods: A Case Study with Neural Networks and Logistic Regression. Int. J. Artif. Intell. Tools 26(6): 1750019:1-1750019:12 (2017) - [c2]Jale Bektas, Turgay Ibrikci:
Hybrid classification procedure using SVM with LR on two distinctive datasets. ICSCA 2017: 68-71
2000 – 2009
- 2009
- [c1]Jale Bektas, Turgay Ibrikci:
Using Threshold Techniques with K-Means for MRI Segmentation. IPCV 2009: 651-655
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