Automatic Design of Neuromarkers for OCD Characterization
Abstract
This paper proposes a new paradigm to discover biomarkers capable of characterizing obsessive-compulsive disorder (OCD). These biomarkers, named neuromarkers, will be obtained through the analysis of sets of magnetic resonance images (MRI) of OCD patients and control subjects. The design of the neuromarkers stems from a method for the automatic discovery of clusters of voxels relevant to OCD recently published by the authors. With these clusters as starting point, we will define the neuromarkers as a set of measurements describing features of these individual regions. The principal goal of the project is to come up with a set of about 50 neuromarkers for OCD characterization that are easy to interpret and handle by the psychiatric community.
Cite
Text
Hinde et al. "Automatic Design of Neuromarkers for OCD Characterization." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2014. doi:10.1007/978-3-662-44848-9_29Markdown
[Hinde et al. "Automatic Design of Neuromarkers for OCD Characterization." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2014.](https://mlanthology.org/ecmlpkdd/2014/hinde2014ecmlpkdd-automatic/) doi:10.1007/978-3-662-44848-9_29BibTeX
@inproceedings{hinde2014ecmlpkdd-automatic,
title = {{Automatic Design of Neuromarkers for OCD Characterization}},
author = {Hinde, Oscar García and Parrado-Hernández, Emilio and Gómez-Verdejo, Vanessa and Martínez-Ramón, Manel and Soriano-Mas, Carles},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2014},
pages = {450-465},
doi = {10.1007/978-3-662-44848-9_29},
url = {https://mlanthology.org/ecmlpkdd/2014/hinde2014ecmlpkdd-automatic/}
}