Title:
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Automated quality control for proton magnetic resonance spectroscopy data using convex non-negative matrix factorization
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Author:
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Mocioiu, Victor; Kyathanahally, Sreenath P.; Arús, Carles; Vellido Alcacena, Alfredo; Julià Sapé, Margarida
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Other authors:
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Universitat Politècnica de Catalunya. Departament de Ciències de la Computació; Universitat Politècnica de Catalunya. SOCO - Soft Computing |
Abstract:
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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. |
Abstract:
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Peer Reviewed |
Subject(s):
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-Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic -Decision support systems -Brain -- Tumors -- Diagnosis -Brain tumors -Magnetic resonance spectroscopy -Convex non-negative matrix factorization -Pattern recognition -Quality control -Machine learning -Sistemes d'ajuda a la decisió -Cervell -- Tumors -- Diagnòstic |
Rights:
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Document type:
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Article - Submitted version Conference Object |
Published by:
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Springer
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