Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Jan 24, 2024
BACKGROUND: Parkinson's disease (PD) ranks as the second most prevalent neurodegenerative disorder globally, and its incidence is rapidly rising. The diagnosis of PD relies on clinical characteristics. Although current treatments aim to alleviate sym...
BACKGROUND: Accurate weed detection is a prerequisite for precise automatic precision herbicide application. Previous research has adopted the laborious and time-consuming approach of manually labeling and processing large image data sets to develop ...
In histopathology practice, scanners, tissue processing, staining, and image acquisition protocols vary from center to center, resulting in subtle variations in images. Vanilla convolutional neural networks are sensitive to such domain shifts. Data a...
Deep learning (DL) in magnetic resonance imaging (MRI) shows excellent performance in image reconstruction from undersampled k-space data. Artifact-free and high-quality MRI reconstruction is essential for ensuring accurate diagnosis, supporting clin...
Learning to perform a perceptual decision task is generally achieved through sessions of effortful practice with feedback. Here, we investigated how passive exposure to task-relevant stimuli, which is relatively effortless and does not require feedba...
BACKGROUND: Osteoporosis is a common age-related disease with disabling consequences, the early diagnosis of which is difficult due to its long and hidden course, which often leads to diagnosis only after a fracture. In this regard, great expectation...
OBJECTIVES: In this paper, an artificial intelligence-based algorithm for predicting the optimal contrast medium dose for computed tomography (CT) angiography of the aorta is presented and evaluated in a clinical study. The prediction of the contrast...
Neural networks : the official journal of the International Neural Network Society
Jan 23, 2024
Multi-view deep neural networks have shown excellent performance on 3D shape classification tasks. However, global features aggregated from multiple views data often lack content information and spatial relationship, which leads to difficult identifi...
Neural networks : the official journal of the International Neural Network Society
Jan 23, 2024
Graph Neural Networks (GNNs) are often viewed as black boxes due to their lack of transparency, which hinders their application in critical fields. Many explanation methods have been proposed to address the interpretability issue of GNNs. These expla...
Neural networks : the official journal of the International Neural Network Society
Jan 23, 2024
An increasing need of running Convolutional Neural Network (CNN) models on mobile devices encourages the studies on efficient and lightweight neural network model. In this paper, an Inverse Residual Multi-Branch Network named IremulbNet is proposed t...
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