@inbook{1dae09e5696b4139990bc1d911ed3fb0,
title = "Automated Quality Control for Proton Magnetic Resonance Spectroscopy Data Using Convex Non-negative Matrix Factorization.",
abstract = "Proton Magnetic Resonance Spectroscopy (1H MRS) has proven its diagnostic potential in a variety of conditions. However, MRS is not yet widely used in clinical routine because of the lack of experts on its diagnostic interpretation. Although data-based decision support systems exist to aid diagnosis, they often take for granted that the data is of good quality, which is not always the case in a real application context. Systems based on models built with bad quality data are likely to underperform in their decision support tasks. In this study, we propose a system to filter out such bad quality data. It is based on convex Non-Negative Matrix Factorization models, used as a dimensionality reduction procedure, and on the use of several classifiers to discriminate between good and bad quality data.",
keywords = "Brain tumors, Convex non-negative matrix factorization, Machine learning, Magnetic resonance spectroscopy, Pattern recognition, Quality control",
author = "Victor Mocioiu and Kyathanahally, {Sreenath P.} and Carles Ar{\'u}s and Alfredo Vellido and Margarida Juli{\`a}-Sap{\'e}",
note = "DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.",
year = "2016",
month = mar,
doi = "10.1007/978-3-319-31744-1_62",
language = "Ingl{\'e}s estadounidense",
isbn = "9783319317434",
volume = "9656",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = " 719–727",
booktitle = "Bioinformatics and Biomedical Engineering. IWBBIO 2016. Lecture Notes in Computer Science()",
}