J
Juan Manuel Górriz
Researcher at University of Granada
Publications - 403
Citations - 8595
Juan Manuel Górriz is an academic researcher from University of Granada. The author has contributed to research in topics: Support vector machine & Computer science. The author has an hindex of 43, co-authored 360 publications receiving 6429 citations. Previous affiliations of Juan Manuel Górriz include University of Cádiz & University of Cambridge.
Papers
More filters
Book ChapterDOI
Support Vector Machines and Neural Networks for the Alzheimer's Disease Diagnosis Using PCA
Miriam Romero López,Javier Ramírez,Juan Manuel Górriz,I. Álvarez,Diego Salas-Gonzalez,Fermín Segovia,Manuel Gómez-Río +6 more
TL;DR: Two pattern recognition methods have been applied to SPECT and PET images in order to obtain an objective classifier which is able to determine whether the patient suffers from AD or not and achieved accuracy results reach 98.33% and 93.41% respectively.
Book ChapterDOI
SPECT Image Classification Techniques for Computer Aided Diagnosis of the Alzheimer Disease
Javier Ramírez,R. Chaves,Juan Manuel Górriz,Miriam Romero López,Diego Salas-Gonzalez,I. Álvarez,Fermín Segovia +6 more
TL;DR: The proposed system yielding a 97% AD diagnosis accuracy, reports clear improvements over existing techniques such as the voxel-as-features (VAF) which yields just a 78% classification accuracy.
Journal ArticleDOI
Granger causality-based information fusion applied to electrical measurements from power transformers
J. Rodríguez-Rivero,Javier Ramírez,Francisco Jesús Martínez-Murcia,Francisco Jesús Martínez-Murcia,Fermín Segovia,Andrés Ortiz,D. Salas,Diego Castillo-Barnes,Ignacio A. Illán,Carlos G. Puntonet,Carmen Jimenez-Mesa,FJ Leiva,S Carillo,John Suckling,Juan Manuel Górriz,Juan Manuel Górriz +15 more
TL;DR: The proposed method is the first attempt to build a data-driven power system model based on G-causality, and analysed directed functional connectivity of electrical measures providing a statistical description of observed responses, and identified the causal structure within data in an exploratory analysis.
Proceedings ArticleDOI
Machine learning for very early Alzheimer's Disease diagnosis; a 18 F-FDG and PiB PET comparison
Ignacio A. Illán,Juan Manuel Górriz,Javier Ramírez,R. Chaves,Fermín Segovia,Miriam Romero López,Diego Salas-Gonzalez,Pablo Padilla,Carlos G. Puntonet +8 more
TL;DR: A machine learning approach based on Principal Component Analysis (PCA) and Support Vector Machine (SVM) to compare the diagnostic accuracy on very early Alzheimer's Disease patients with 18F FDG and Pittsburg Compound B (PiB) PET imaging is shown.
Book ChapterDOI
Retinal Blood Vessel Segmentation by Multi-channel Deep Convolutional Autoencoder
Andrés Ortiz,Javier Ramírez,Ricardo Cruz-Arándiga,María J. García-Tarifa,Francisco Jesús Martínez-Murcia,Juan Manuel Górriz +5 more
TL;DR: This paper deals with an important stage of the retina image processing for a diagnosis tool which aims to show the blood vessel structure using a deep convolutional neural network, that avoids any preprocessing stage such as gray scale conversion, histogram equalization, and other image transformations that determine the final result.