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Titlebook: Artificial Intelligence in Neuroscience: Affective Analysis and Health Applications; 9th International Wo José Manuel Ferrández Vicente,Jos

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發(fā)表于 2025-3-30 11:24:17 | 只看該作者
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發(fā)表于 2025-3-30 17:28:39 | 只看該作者
Kristalle und andere feste Stoffe,MR images are created with the help of the cycle generative adversarial network (GAN) model at this step. Finally, pretrained models including EfficientNet B3, EfficientNet V2, HrNet, ResNetrs50, ResNest50d, and ResNet 50d have been used to classify the input data. Among pretrained methods, the Effi
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發(fā)表于 2025-3-30 22:46:42 | 只看該作者
Benjamin Bahr,J?rg Resag,Kristin Riebe. The usefulness of this method has been assessed with images from the Parkinson’s Progression Markers Initiative, demonstrating that differences between the dopaminergic regions of both hemispheres lead to a high performance when classifying controls . Parkinson’s disease patients.
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發(fā)表于 2025-3-31 04:22:53 | 只看該作者
https://doi.org/10.1007/978-3-662-67904-3stical Agnostic Mapping (SAM) proposal. Results obtained suggest that there are no relevant ROIs in GM MRI imaging contrary to other modalities like the FP-CIT SPECT scans evaluated on the striatum region.
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發(fā)表于 2025-3-31 07:38:43 | 只看該作者
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發(fā)表于 2025-3-31 11:47:18 | 只看該作者
Automatic Classification System for?Diagnosis of?Cognitive Impairment Based on?the?Clock-Drawing Tesnto a Convolutional Neural Network (CNN), which is used to identify the informative patterns within the CDT drawings that are relevant for the assessment of the patient’s cognitive status. Performance is evaluated in a real context where differentiating between CI patients and controls. The proposed
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發(fā)表于 2025-3-31 15:16:34 | 只看該作者
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