AIMC Topic: Neural Networks, Computer

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Deep learning for discrimination of active and inactive lesions in multiple sclerosis using non-contrast FLAIR MRI: A multicenter study.

Multiple sclerosis and related disorders Apr 21, 2024
BACKGROUND: Within the domain of multiple sclerosis (MS), the precise discrimination between active and inactive lesions bears immense significance. Active lesions are enhanced on T1-weighted MRI images after administration of gadolinium-based contra...
Image Interpretation, Computer-Assisted Adult Sensitivity and Specificity Magnetic Resonance Imaging Middle Aged Multiple Sclerosis Deep Learning Male Brain Humans Neural Networks, Computer Female
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MRI super-resolution using similarity distance and multi-scale receptive field based feature fusion GAN and pre-trained slice interpolation network.

Magnetic resonance imaging Apr 21, 2024
Challenges arise in achieving high-resolution Magnetic Resonance Imaging (MRI) to improve disease diagnosis accuracy due to limitations in hardware, patient discomfort, long acquisition times, and high costs. While Convolutional Neural Networks (CNNs...
Brain Imaging, Three-Dimensional Magnetic Resonance Imaging Image Processing, Computer-Assisted Neural Networks, Computer Algorithms Humans
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Construction of deep learning-based convolutional neural network model for automatic detection of fluid hysteroscopic endometrial micropolyps in infertile women with chronic endometritis.

European journal of obstetrics, gynecology, and reproductive biology Apr 21, 2024
OBJECTIVE(S): Chronic endometritis (CE) is a localized mucosal inflammatory disorder associated with female infertility of unknown etiology, endometriosis, tubal factors, repeated implantation failure, and recurrent pregnancy loss, along with atypica...
Hysteroscopy Chronic Disease Endometritis Humans Deep Learning Neural Networks, Computer Infertility, Female Female Endometrium Adult
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VENet: Variational energy network for gland segmentation of pathological images and early gastric cancer diagnosis of whole slide images.

Computer methods and programs in biomedicine Apr 21, 2024
BACKGROUND AND OBJECTIVE: Gland segmentation of pathological images is an essential but challenging step for adenocarcinoma diagnosis. Although deep learning methods have recently made tremendous progress in gland segmentation, they have not given sa...
Stomach Neoplasms Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Algorithms Image Interpretation, Computer-Assisted Adenocarcinoma Early Detection of Cancer Humans
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Investigation of the effectiveness of a classification method based on improved DAE feature extraction for hepatitis C prediction.

Scientific reports Apr 21, 2024
Hepatitis C, a particularly dangerous form of viral hepatitis caused by hepatitis C virus (HCV) infection, is a major socio-economic and public health problem. Due to the rapid development of deep learning, it has become a common practice to apply de...
Hepatitis C Humans Neural Networks, Computer Deep Learning Hepacivirus Algorithms
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DeepReg: a deep learning hybrid model for predicting transcription factors in eukaryotic and prokaryotic genomes.

Scientific reports Apr 21, 2024
Deep learning models (DLMs) have gained importance in predicting, detecting, translating, and classifying a diversity of inputs. In bioinformatics, DLMs have been used to predict protein structures, transcription factor-binding sites, and promoters. ...
Deep Learning Computational Biology Transcription Factors Neural Networks, Computer Genome Prokaryotic Cells Eukaryotic Cells Binding Sites Eukaryota
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Multi-scale full spike pattern for semantic segmentation.

Neural networks : the official journal of the International Neural Network Society Apr 20, 2024
Spiking neural networks (SNNs), as the brain-inspired neural networks, encode information in spatio-temporal dynamics. They have the potential to serve as low-power alternatives to artificial neural networks (ANNs) due to their sparse and event-drive...
Algorithms Deep Learning Action Potentials Neurons Models, Neurological Humans Neural Networks, Computer Semantics
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Reconstructing transient pressures in pipe networks from local observations by using physics-informed neural networks.

Water research Apr 20, 2024
Reconstructing transient states presents significant challenges, particularly within complex pipe networks. These challenges arise due to nonlinear behaviours, inherent uncertainties in the system, and limitations in data availability. This work prop...
Water Supply Models, Theoretical Pressure Neural Networks, Computer
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Differentiating stable and unstable protein using convolution neural network and molecular dynamics simulations.

Computational biology and chemistry Apr 20, 2024
Protein stability is a critical aspect of molecular biology and biochemistry, hinges on an intricate balance of thermodynamic and structural factors. Determining protein stability is crucial for understanding and manipulating biological machineries, ...
Protein Stability Machine Learning Neural Networks, Computer Thermodynamics Proteins Molecular Dynamics Simulation
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Automatic classification of dog barking using deep learning.

Behavioural processes Apr 20, 2024
Barking and other dog vocalizations have acoustic properties related to emotions, physiological reactions, attitudes, or some particular internal states. In the field of intelligent audio analysis, researchers use methods based on signal processing a...
Neural Networks, Computer Female Deep Learning Dogs Vocalization, Animal Animals Male
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