Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/23395

Title: A Case-Based Reasoning Approach to GBM Evolution
Authors: Mendonça, Ana
Pereira, Joana
Reis, Rita
Alves, Victor
Abelha, António
Ferraz, Filipa
Neves, João
Ribeiro, Jorge
Vicente, Henrique
Neves, José
Keywords: Artificial Intelligence
GlioBlastoma Multiforme
Logic Programming
Knowledge Representation and Reasoning
Case Based Reasoning
Issue Date: 2018
Publisher: Springer
Citation: Mendonça, A., Pereira, J., Reis, R., Alves, V., Abelha, A., Ferraz, F., Neves, J., Ribeiro, J., Vicente, H., Neves, J. A Case-Based Reasoning Approach to GBM Evolution. Lecture Notes in Computer Science, 11056, 489–498, 2018.
Abstract: GlioBastoma Multiforme (GBM) is an aggressive primary brain tumor characterized by a heterogeneous cell population that is genetically unstable and resistant to chemotherapy. Indeed, despite advances in medicine, patients diagnosed with GBM have a median survival of just one year. Magnetic Resonance Imaging (MRI) is the most widely used imaging technique for determining the location and size of brain tumors. Indisputably, this technique plays a major role in the diagnosis, treatment planning, and prognosis of GBM. Therefore, this study proposes a new Case Based Reasoning approach to problem solving that attempts to predict a patient’s GBM volume after five months of treatment based on features extracted from MR images and patient attributes such as age, gender, and type of treatment.
URI: https://link.springer.com/chapter/10.1007/978-3-319-98446-9_46
http://hdl.handle.net/10174/23395
ISSN: 0302-9743 (print)
1611-3349 (electronic)
Type: article
Appears in Collections:CQE - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica
QUI - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica

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