May 27, 2017 · This work introduces a supervised feature extraction approach using a dGSN as a deep learning machine for automatic MRI-based dementia diagnosis ...
Mar 30, 2024 · Pattern recognition methods, applied to dementia diagnosis, improve either the feature extraction or the classifier stage. Particularly, deep ...
MRI-Based Feature Extraction Using Supervised General Stochastic Networks in Dementia Diagnosis. https://doi.org/10.1007/978-3-319-59740-9_36 ·.
MRI-based feature extraction using supervised general stochastic networks in dementia diagnosis. D Collazos-Huertas, A Tobar-Rodriguez, D Cárdenas-Peña ...
Brain MRI morphological patterns extraction tool based on Extreme ...
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This work proposes a deep supervised feature extraction approach using General Stochastic Networks through a supervised layer-wise non-linear mapping ...
Feb 2, 2023 · The SVM with a polynomial kernel obtained the best dementia diagnosis accuracy of 88.59 percent. However, the SVM training accuracy is lower ...
Apr 11, 2022 · In this study, we propose a pre-trained CNN deep learning model ResNet50 as an automatic feature extraction method for diagnosing Alzheimer's disease using MRI ...
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The book aims to provide a deeper understanding of the synergistic impact of Artificial intelligence (AI) and the Internet of Things (IoT) for disease ...
Using DL to extract features from MRI helps obtain results of 93%. Study [20] proposed a computational model based on an ANN to determine the necessary ...
MRI-Based Feature Extraction Using Supervised General Stochastic Networks in Dementia Diagnosis · Computer Science, Medicine. IWINAC · 2017.