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Springer (part of Springer Nature), Neural Computing and Applications, 5(32), p. 1231-1238, 2018

DOI: 10.1007/s00521-018-3503-4

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A methodology for detecting relevant single nucleotide polymorphism in prostate cancer with multivariate adaptive regression splines and backpropagation artificial neural networks

Journal article published in 2018 by Juan Enrique Sánchez Lasheras, Carmen González Donquiles, Paulino José García Nieto, José Juan Jiménez Moleon, Dolores Salas, Sergio Luis Suárez Gómez, Antonio J. Molina de la Torre, Joaquín González-Nuevo ORCID, Laura Bonavera ORCID, Jorge Carballido Landeira, Francisco Javier de Cos Juez
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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