An evolutionary artificial neural networks approach for breast cancer diagnosis
By Hussein A. Abbass. Artif. Intell. Medicine, 2002
412 citations recorded by the source corpus.
Subfields: Artificial Intelligence
View Paper: https://www.semanticscholar.org/paper/bbbe5535472e8c8e019c72c1dade4eedeef333c3
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
- Ferrante Neri
- Carlos Cotta
- Yew-Soon Ong
- Meng-Hiot Lim
- Xianshun Chen
- A. Ramli
- Syamsiah Mashohor
- M. Iqbal Bin Saripan
Citations in the corpus
- Computer-aided detection/diagnosis of breast cancer in mammography and ultrasound: a review. (2013, methodology): “A prediction framework for breast cancer diagnosis based on evolutionary ANN is available in the related literature [58].”
- Memetic Computation—Past, Present & Future [Research Frontier] (2010, background): “…problems [22], optimal control systems of permanent magnet synchronous motor [23], datamining , machine learning and artificial neural networks [24], dynamic optimization problems [23] [25], computationally expensive environments [20] [26], robust design [26], fuzzy modeling [27] [28], and…”
- Memetic algorithms and memetic computing optimization: A literature review (2012, background): “In [1] a memetic approach is proposed for a neural network training in the context of a medical application.”
- Predicting breast cancer survivability: a comparison of three data mining methods (2005, methodology): “In a 4 D. Delen et al. DTD 5 related study, Abbass [25] used an evolutionary ANN (EANN) for breast cancer diagnosis.”