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IEEE Transactions on Neural Networks and Learning Systems|August 6, 2014
Complex support vector machines for regression and quaternary classificationPantelis Bouboulis, Sergios Theodoridis, Charalampos Mavroforakis, et al.
European Journal of Radiology|March 31, 2005
Significance analysis of qualitative mammographic features, using linear classifiers, neural networks and support vector machinesMichael Mavroforakis, Harris Georgiou, Nikos Dimitropoulos, et al.
Artificial Intelligence in Medicine|August 24, 2007
Multi-scaled morphological features for the characterization of mammographic masses using statistical classification schemesHarris Georgiou, Michael Mavroforakis, Nikos Dimitropoulos, et al.
Neuroimage|November 14, 2021
Enhanced design matrix for task-related fMRI data analysisManuel Morante, Yannis Kopsinis, Christos Chatzichristos, et al.
IEEE Transactions on Neural Networks and Learning Systems|March 3, 2025
Sparsity-Aware Distributed Learning for Gaussian Processes With Linear Multiple KernelRichard Cornelius Suwandi, Zhidi Lin, Feng Yin, et al.
Plos One|July 2, 2020
Emojis influence autobiographical memory retrieval from reading words: An fMRI-based studyChristos Chatzichristos, Manuel Morante, Nikolaos Andreadis, et al.
Artificial Intelligence in Medicine|May 24, 2006
Mammographic masses characterization based on localized texture and dataset fractal analysis using linear, neural and support vector machine classifiersMichael E Mavroforakis, Harris V Georgiou, Nikos Dimitropoulos, et al.
Computer Methods and Programs in Biomedicine|February 11, 2011
A fully automated scheme for mammographic segmentation and classification based on breast density and asymmetryStylianos D Tzikopoulos, Michael E Mavroforakis, Harris V Georgiou, et al.
Human Brain Mapping|November 22, 2021
Early soft and flexible fusion of electroencephalography and functional magnetic resonance imaging via double coupled matrix tensor factorization for multisubject group analysisChristos Chatzichristos, Eleftherios Kofidis, Wim Van Paesschen, et al.
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