🐬
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Classification of EEG signals using relative wavelet energy and artificial neural networks
Ling Guo,
D. Rivero,
José Antonio Seoane Fernández,
A. Pazos
|
7 |
2009 |
7 🐬
|
🦁
|
A pathway-based data integration framework for prediction of disease progression
José Antonio Seoane Fernández,
I. Day,
Tom R. Gaunt,
C. Campbell
|
6 |
2013 |
6 🦁
|
🐬
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RRegrs: an R package for computer-aided model selection with multiple regression models
G. Tsiliki,
C. Munteanu,
José Antonio Seoane Fernández,
C. Fernandez-Lozano,
H. Sarimveis,
Egon Willighagen
|
5 |
2015 |
5 🐬
|
🦁
|
Canonical Correlation Analysis for Gene-Based Pleiotropy Discovery
José Antonio Seoane Fernández,
C. Campbell,
I. Day,
J. Casas,
Tom R. Gaunt
|
5 |
2014 |
5 🦁
|
🐜
|
Breast density classification to reduce false positives in CADe systems
7 auth.
Noelia Vállez,
Gloria Bueno García,
O. Déniz-Suárez,
J. Dorado,
José Antonio Seoane Fernández,
A. Pazos,
...
Carlos Pastor
|
5 |
2014 |
5 🐜
|
🐬
|
Texture classification using feature selection and kernel-based techniques
C. Fernandez-Lozano,
José Antonio Seoane Fernández,
M. Gestal,
Tom R. Gaunt,
J. Dorado,
Colin Campbell
|
5 |
2015 |
5 🐬
|
🐬
|
Classification of signaling proteins based on molecular star graph descriptors using Machine Learning models
C. Fernandez-Lozano,
Ruben F. Cuinas,
José Antonio Seoane Fernández,
Enrique Fernández-Blanco,
J. Dorado,
C. Munteanu
|
4 |
2015 |
4 🐬
|
🐬
|
Using genetic algorithms and k-nearest neighbour for automatic frequency band selection for signal classification
D. Rivero,
Ling Guo,
José Antonio Seoane Fernández,
J. Dorado
|
3 |
2012 |
3 🐬
|