| A survey of multiple classifier systems as hybrid systems M Woźniak, M Grana, E Corchado Information Fusion 16, 3-17, 2014 | 1151 | 2014 |
| Model‐based analysis of multishell diffusion MR data for tractography: How to get over fitting problems S Jbabdi, SN Sotiropoulos, AM Savio, M Graña, TEJ Behrens Magnetic resonance in medicine 68 (6), 1846-1855, 2012 | 439 | 2012 |
| Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications JM Górriz, J Ramírez, A Ortiz, FJ Martinez-Murcia, F Segovia, J Suckling, ... Neurocomputing 410, 237-270, 2020 | 247 | 2020 |
| Predictive models for hospital readmission risk: A systematic review of methods A Artetxe, A Beristain, M Grana Computer methods and programs in biomedicine 164, 49-64, 2018 | 190 | 2018 |
| Computer aided diagnosis system for Alzheimer disease using brain diffusion tensor imaging features selected by Pearson's correlation M Graña, M Termenon, A Savio, A Gonzalez-Pinto, J Echeveste, JM Pérez, ... Neuroscience letters 502 (3), 225-229, 2011 | 155 | 2011 |
| Gentle introduction to artificial intelligence for high-school students using scratch J Estevez, G Garate, M Graña IEEE access 7, 179027-179036, 2019 | 152 | 2019 |
| Energy balance in feedback synchronization of chaotic systems C Sarasola, FJ Torrealdea, A d’Anjou, A Moujahid, M Graña Physical Review E 69 (1), 011606, 2004 | 120 | 2004 |
| face recognition algorithms I Marques, M Grana | 106 | |
| Two lattice computing approaches for the unsupervised segmentation of hyperspectral images M Grana, I Villaverde, JO Maldonado, C Hernandez Neurocomputing 72 (10-12), 2111-2120, 2009 | 103 | 2009 |
| Extreme learning machines for soybean classification in remote sensing hyperspectral images R Moreno, F Corona, A Lendasse, M Graña, LS Galvão Neurocomputing 128, 207-216, 2014 | 100 | 2014 |
| Semantically enhanced network analysis for influencer identification in online social networks SA Rios, F Aguilera, JD Nuñez-Gonzalez, M Graña Neurocomputing 326, 71-81, 2019 | 94 | 2019 |
| Computer aided diagnosis of schizophrenia on resting state fMRI data by ensembles of ELM D Chyzhyk, A Savio, M Graña Neural Networks 68, 23-33, 2015 | 92 | 2015 |
| Endmember extraction methods: A short review MA Veganzones, M Grana International conference on knowledge-based and intelligent information and …, 2008 | 92 | 2008 |
| Impairment of functional integration of the default mode network correlates with cognitive outcome at three months after stroke R Dacosta‐Aguayo, M Grana, Y Iturria‐Medina, M Fernández‐Andújar, ... Human brain mapping 36 (2), 577-590, 2015 | 87 | 2015 |
| Evolutionary ELM wrapper feature selection for Alzheimer's disease CAD on anatomical brain MRI D Chyzhyk, A Savio, M Graña Neurocomputing 128, 73-80, 2014 | 87 | 2014 |
| Computational approaches to explainable artificial intelligence: advances in theory, applications and trends JM Górriz, I Álvarez-Illán, A Álvarez-Marquina, JE Arco, M Atzmueller, ... Information Fusion 100, 101945, 2023 | 86 | 2023 |
| On the potential contributions of hybrid intelligent approaches to multicomponent robotic system development RJ Duro, M Graña, J de Lope Information Sciences 180 (14), 2635-2648, 2010 | 82 | 2010 |
| Morphological scale spaces and associative morphological memories: Results on robustness and practical applications B Raducanu, M Graña, FX Albizuri Journal of Mathematical Imaging and Vision 19 (2), 113-131, 2003 | 81 | 2003 |
| Discrimination of schizophrenia auditory hallucinators by machine learning of resting-state functional MRI D Chyzhyk, M Graña, D Öngür, AK Shinn International journal of neural systems 25 (03), 1550007, 2015 | 79 | 2015 |
| A lattice computing approach to Alzheimer’s disease computer assisted diagnosis based on MRI data GA Papakostas, A Savio, M Graña, VG Kaburlasos Neurocomputing 150, 37-42, 2015 | 76 | 2015 |
Alexandre SavioKlinikum rechts der Isar, Technische Universität München, GermanyAdresse e-mail validée de tum.de
