AIMC Topic: Neural Networks, Computer

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Two-stage convolutional neural network for segmentation and detection of carotid web on CT angiography.

Journal of neurointerventional surgery
BACKGROUND: Carotid web (CaW) is a risk factor for ischemic stroke, mainly in young patients with stroke of undetermined etiology. Its detection is challenging, especially among non-experienced physicians.

An analytic hierarchy process combined with artificial neural network model to evaluate sustainable sludge treatment scenarios.

Waste management (New York, N.Y.)
Sludge management in China faces critical environmental, economic, and technical challenges, necessitating urgent optimal management strategy selection. Given the limited number of comprehensive studies on sludge management, quantitative decision-mak...

ENsiRNA: A Multimodality Method for siRNA-mRNA and Modified siRNA Efficacy Prediction Based on Geometric Graph Neural Network.

Journal of molecular biology
With the rise of small interfering RNA (siRNA) as a therapeutic tool, effective siRNA design is crucial. Current methods often emphasize sequence-related features, overlooking structural information. To address this, we introduce ENsiRNA, a multimoda...

PLPTP: A Motif-based Interpretable Deep Learning Framework Based on Protein Language Models for Peptide Toxicity Prediction.

Journal of molecular biology
Peptide toxicity prediction holds significant importance in drug development and biotechnology, as accurately identifying toxic peptide sequences is crucial for designing safer peptide-based drugs. This study proposes a deep learning-based model for ...

Supervised and unsupervised learning for lung perfusion data segmentation in electrical impedance tomography.

Biomedical physics & engineering express
: Effective lung gas exchange relies on the balance between alveolar ventilation and perfusion, which can be disrupted in mechanically ventilated patients. Lung perfusion assessment using electrical impedance tomography (EIT) typically involves a sud...

The combined multilayer perceptron and logistic regression (MLP-LR) method better predicted the spread of Hyphantria cunea (Lepidoptera: Erebidae).

Journal of economic entomology
Hyphantria cunea (Lepidoptera: Erebidae) is one of the pests that pose a serious threat to forest and agronomic crops in China. Its spread is influenced by various factors, including environmental factors and anthropogenic factors, and the available ...

Deployment of an Artificial Intelligence Histology Tool to Aid Qualitative Assessment of Histopathology Using the Nancy Histopathology Index in Ulcerative Colitis.

Inflammatory bowel diseases
BACKGROUND: Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized by increased stool frequency, rectal bleeding, and urgency. To streamline the quantitative assessment of histopathology using the Nancy Index in UC patients, we...

Interpretable Multimodal Deep Ensemble Framework Dissecting Bloodbrain Barrier Permeability with Molecular Features.

The journal of physical chemistry letters
Blood-brain barrier permeability (BBBP) prediction plays a critical role in the drug discovery process, particularly for compounds targeting the central nervous system. While machine learning (ML) has significantly advanced the prediction of BBBP, th...

Artificial neural networks for magnetoencephalography: a review of an emerging field.

Journal of neural engineering
. Magnetoencephalography (MEG) is a cutting-edge neuroimaging technique that measures the intricate brain dynamics underlying cognitive processes with an unparalleled combination of high temporal and spatial precision. While MEG data analytics have t...