An expert system for detection of breast cancer based on association rules and neural network

By Murat Karabatak, M. C. Ince. Expert systems with applications, 2009

537 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems

View Paper: https://www.semanticscholar.org/paper/a7f5a8fb71f6c939a876dcd2446ea4daeb00408e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. G. Yacalis
2. Bo Yang
3. Pierre Gentine
4. Da-you Liu
5. Jie Liu
6. G. Reinaudi
7. Stephan Rasp
8. Michael S. Pritchard

In Computer Vision and Pattern Recognition

1. Bo Yang
2. Da-you Liu
3. Jie Liu
4. Stephan Rasp
5. Huiling Chen

In Information Systems

1. Bo Yang
2. Da-you Liu
3. Jie Liu
4. Huiling Chen

Citations in the corpus

• A support vector machine classifier with rough set-based feature selection for breast cancer diagnosis (2011, methodology): “And in Karabatak and Ince (2009), the method combined with association rules and neural network were utilized and accuracy of 95.6% was obtained.”
• Cartesian genetic programming encoded artificial neural networks: a comparison using three benchmarks (2013, unknown): “AR + ANN [14] No 2.”
• Could Machine Learning Break the Convection Parameterization Deadlock? (2018, background): “, 2012], 129 object recognition and detection, medical detection of cancers [Khan et al., 2001; Zhou et al., 130 2002; Karabatak and Ince, 2009], and genomics.”