AIMC Topic: Deep Learning

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Exploring Longitudinal Cough, Breath, and Voice Data for COVID-19 Progression Prediction via Sequential Deep Learning: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: Recent work has shown the potential of using audio data (eg, cough, breathing, and voice) in the screening for COVID-19. However, these approaches only focus on one-off detection and detect the infection, given the current audio sample, b...

Music Emotion Classification Method Based on Deep Learning and Explicit Sparse Attention Network.

Computational intelligence and neuroscience
In order to improve the accuracy of music emotion recognition and classification, this study combines an explicit sparse attention network with deep learning and proposes an effective emotion recognition and classification method for complex music da...

Feature Extraction of Athlete's Post-Match Psychological and Emotional Changes Based on Deep Learning.

Computational intelligence and neuroscience
Athletes have had to deal with significant shifts in the way they think about psychology and emotion before and after attending a match in their respective fields. It has become increasingly difficult for players of any sport to overcome these differ...

Multisemantic Level Patch Merger Vision Transformer for Diagnosis of Pneumonia.

Computational and mathematical methods in medicine
The most popular test for pneumonia, a serious health threat to children, is chest X-ray imaging. However, the diagnosis of pneumonia relies on the expertise of experienced radiologists, and the scarcity of medical resources has forced us to conduct ...

Lung-Optimized Deep-Learning-Based Reconstruction for Ultralow-Dose CT.

Academic radiology
RATIONALE AND OBJECTIVES: To evaluate the image properties of lung-specialized deep-learning-based reconstruction (DLR) and its applicability in ultralow-dose CT (ULDCT) relative to hybrid- (HIR) and model-based iterative-reconstructions (MBIR).

Size-adaptive mediastinal multilesion detection in chest CT images via deep learning and a benchmark dataset.

Medical physics
PURPOSE: Many deep learning methods have been developed for pulmonary lesion detection in chest computed tomography (CT) images. However, these methods generally target one particular lesion type, that is, pulmonary nodules. In this work, we intend t...

Simultaneously optimizing sampling pattern for joint acceleration of multi-contrast MRI using model-based deep learning.

Medical physics
BACKGROUND: Acceleration of MR imaging (MRI) is a popular research area, and usage of deep learning for acceleration has become highly widespread in the MR community. Joint acceleration of multiple-acquisition MRI was proven to be effective over a si...

Deep learning for centre manifold reduction and stability analysis in nonlinear systems.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Bifurcations cause large qualitative and quantitative changes in the dynamics of nonlinear systems with slowly varying parameters. These changes most often are due to modifications that occur in a low-dimensional subspace of the overall system dynami...

DeepRF: A deep learning method for predicting metabolic pathways in organisms based on annotated genomes.

Computers in biology and medicine
The rapid increase of metabolomics has led to an increasing focus on metabolic pathway modeling and reconstruction. In particular, reconstructing an organism's metabolic network based on its genome sequence is a key challenge in systems biology. The ...