@article {7460246,
	title = {A computer-aided diagnosis system with EEG based on the P3b wave during an auditory odd-ball task in schizophrenia},
	journal = {IEEE Transactions on Biomedical Engineering},
	volume = {PP},
	number = {99},
	year = {2016},
	pages = {1-1},
	abstract = {Objective: To design a Computer-aided diagnosis (CAD) system using an optimized methodology over the P3b wave in order to objectively and accurately discriminate between healthy controls (HC) and schizophrenic subjects (SZ). Methods: We train, test, analyze, and compare various machine learning classification approaches optimized in terms of the correct classification rate (CCR), the degenerated Youden{\textquoteright}s index (DYI) and the area under the receiver operating curve (AUC). CAD system comprises five stages: electroencephalography (EEG) preprocessing, feature extraction, seven electrode groupings, discriminant feature selection, and binary classification. Results: With two optimal combinations of electrode grouping, filtering, feature selection algorithm, and classification machine, we get either a mean CCR = 93.42\%, specificity = 0.9673, sensitivity = 0.8727, DYI = 0.9188, and AUC = 0.9567 (total-15 Hz-J5-MLP), or a mean CCR = 92.23\%, specificity = 0.9499, sensitivity = 0.8838, DYI = 0.9162, and AUC = 0.9807 (right hemisphere-35 Hz-J5-SVM), which to our knowledge are higher than those available to date. Conclusions: We have verified that a more restrictive low-pass filtering achieves higher CCR as compared to others at higher frequencies in the P3b wave. In addition, results validate previous hypothesis about the importance of the parietal-temporal region, associated with memory processing, allowing us to identify powerful {feature,electrode} pairs in the diagnosis of schizophrenia, achieving higher CCR and AUC in classification of both right and left Hemispheres, and parietal-temporal EEG signals, like, for instance, the {PSE, P4} pair (J5 and mutual information feature selection). Significance: Diagnosis of schizophrenia is made thoroughly by psychiatrists but as any human-based decision that has a subjective component. This CAD system provides the human expert with an objective complimentary measure to help him in diagnosing schizophrenia.},
	keywords = {Computer aided diagnosis, Design automation, Electrodes, Electroencephalography, Feature extraction, Indexes, Sensitivity},
	issn = {0018-9294},
	doi = {10.1109/TBME.2016.2558824},
	url = {https://ieeexplore.ieee.org/abstract/document/7460246},
	author = {L. Santos-Mayo and Luis Miguel San-Jose-Revuelta and J I Arribas}
}
@article {san2008efficient,
	title = {Efficient tracking of MR tensor fields using a multilayer neural network},
	journal = {IAENG International Journal of Computer Science},
	volume = {35},
	number = {1},
	year = {2008},
	pages = {129{\textendash}139},
	author = {Luis Miguel San-Jose-Revuelta and Marcos Martin-Fernandez and Carlos Alberola-Lopez}
}
@proceedings {san2008ga,
	title = {A GA-based Approach for Parameter Estimation in DT-MRI Tracking Algorithms},
	volume = {1},
	year = {2008},
	author = {Luis Miguel San-Jose-Revuelta and Marcos Martin-Fernandez and Carlos Alberola-Lopez}
}
@conference {san2007neural,
	title = {Neural Network-Assisted Fiber Tracking of Synthetic and White Matter DT-MR Images.},
	booktitle = {World Congress on Engineering},
	year = {2007},
	pages = {618{\textendash}623},
	author = {Luis Miguel San-Jose-Revuelta and Marcos Martin-Fernandez and Carlos Alberola-Lopez}
}
@conference {san2007new,
	title = {A new proposal for 3D fiber tracking in synthetic diffusion tensor magnetic resonance images},
	booktitle = {Signal Processing and Its Applications, 2007. ISSPA 2007. 9th International Symposium on},
	year = {2007},
	pages = {1{\textendash}4},
	publisher = {IEEE},
	organization = {IEEE},
	author = {Luis Miguel San-Jose-Revuelta and Marcos Martin-Fernandez and Carlos Alberola-Lopez}
}
@proceedings {san2006new,
	title = {A new method for fiber tractography in diffusion tensor magnetic resonance images},
	volume = {6},
	year = {2006},
	pages = {380{\textendash}385},
	author = {Luis Miguel San-Jose-Revuelta and Marcos Martin-Fernandez and Carlos Alberola-Lopez}
}
