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Please use this identifier to cite or link to this item: http://hdl.handle.net/10651/33362

Title: On the prediction of Hodgkin lymphoma treatment response
Author(s): Andrés Galiana, Enrique Juan de
Fernández Martínez, Juan Luis
Luaces Rodríguez, Óscar
Coz Velasco, Juan José del
Fernández, R.
Solano, Julia
Nogués, E. A.
González Rodríguez, Ana Pilar
Keywords: Hodgkin lymphoma
Treatment response
Machine learning
Issue date: 2015
Publisher version: http://dx.doi.org/10.1007/s12094-015-1285-z
Citation: Clinical and Translational Oncology, 17(8), p. (2015); doi:10.1007/s12094-015-1285-z
Format extent: p. 612-619
Abstract: The cure rate in Hodgkin lymphoma is high, but the response along with treatment is still unpredictable and highly variable among patients. Detecting those patients who do not respond to treatment at early stages could bring improvements in their treatment. This research tries to identify the main biological prognostic variables currently gathered at diagnosis and design a simple machine learning methodology to help physicians improve the treatment response assessment
URI: http://hdl.handle.net/10651/33362
ISSN: 1699-048X
Sponsored: Enrique J. de Andrés was supported by the Spanish Ministerio de Economía y Competitividad (Grant TIN2011-23558), and the medical analysis was supported by the Fondo de Investigaciones Sanitarias (Instituto Carlos III-Grant PI12/01280). No other financial support has been received to perform this retrospective analysis
Project id.: MEC/TIN2011-23558
Fondo de Investigaciones Sanitarias-Instituto Carlos III/PI12-01280
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