AIMC Topic: Neural Networks, Computer

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Interpreting optimised data-driven solution with explainable artificial intelligence (XAI) for water quality assessment for better decision-making in pollution management.

Environmental science and pollution research international Jun 17, 2024
In Saudi Arabia, water pollution and drinking water scarcity pose a major challenge and jeopardise the achievement of sustainable development goals. The urgent need for rapid and accurate monitoring and assessment of water quality requires sophistica...
Environmental Monitoring Artificial Intelligence Decision Making Water Pollution Machine Learning Water Quality Saudi Arabia Neural Networks, Computer
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UDBRNet: A novel uncertainty driven boundary refined network for organ at risk segmentation.

PloS one Jun 17, 2024
Organ segmentation has become a preliminary task for computer-aided intervention, diagnosis, radiation therapy, and critical robotic surgery. Automatic organ segmentation from medical images is a challenging task due to the inconsistent shape and siz...
Algorithms Image Processing, Computer-Assisted Tomography, X-Ray Computed Organs at Risk Humans Uncertainty Lung Neural Networks, Computer
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BrainLossNet: a fast, accurate and robust method to estimate brain volume loss from longitudinal MRI.

International journal of computer assisted radiology and surgery Jun 16, 2024
PURPOSE: MRI-derived brain volume loss (BVL) is widely used as neurodegeneration marker. SIENA is state-of-the-art for BVL measurement, but limited by long computation time. Here we propose "BrainLossNet", a convolutional neural network (CNN)-based m...
Humans Adult Male Middle Aged Neural Networks, Computer Brain Female Organ Size Imaging, Three-Dimensional Magnetic Resonance Imaging
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Accurate prediction of drug combination risk levels based on relational graph convolutional network and multi-head attention.

Journal of translational medicine Jun 16, 2024
BACKGROUND: Accurately identifying the risk level of drug combinations is of great significance in investigating the mechanisms of combination medication and adverse reactions. Most existing methods can only predict whether there is an interaction be...
Computer Graphics Drug Combinations Drug Interactions Drug-Related Side Effects and Adverse Reactions Reproducibility of Results Risk Assessment Humans Neural Networks, Computer
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A deep-learning-based model for assessment of autoimmune hepatitis from histology: AI(H).

Virchows Archiv : an international journal of pathology Jun 15, 2024
Histological assessment of autoimmune hepatitis (AIH) is challenging. As one of the possible results of these challenges, nonclassical features such as bile-duct injury stays understudied in AIH. We aim to develop a deep learning tool (artificial int...
Biopsy Image Interpretation, Computer-Assisted Hepatitis, Autoimmune Female Deep Learning Reproducibility of Results Liver Aged Predictive Value of Tests Adult Humans Male Neural Networks, Computer Middle Aged
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Omnidirectional image super-resolution via position attention network.

Neural networks : the official journal of the International Neural Network Society Jun 15, 2024
For convenient transmission, omnidirectional images (ODIs) usually follow the equirectangular projection (ERP) format and are low-resolution. To provide better immersive experience, omnidirectional image super resolution (ODISR) is essential. However...
Image Processing, Computer-Assisted Attention Humans Neural Networks, Computer Algorithms
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Deep recognition of rice disease images: how many training samples do we really need?

Journal of the science of food and agriculture Jun 15, 2024
BACKGROUND: With the rapid development of deep learning, the recognition of rice disease images using deep neural networks has become a hot research topic. However, most previous studies only focus on the modification of deep learning models, while l...
Plant Leaves Oryza Plant Diseases Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted
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Brain-computer interfaces inspired spiking neural network model for depression stage identification.

Journal of neuroscience methods Jun 15, 2024
BACKGROUND: Depression is a global mental disorder, and traditional diagnostic methods mainly rely on scales and subjective evaluations by doctors, which cannot effectively identify symptoms and even carry the risk of misdiagnosis. Brain-Computer Int...
Electroencephalography Brain-Computer Interfaces Depression Models, Neurological Action Potentials Humans Neural Networks, Computer Brain Adult Deep Learning
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Patient stratification based on the risk of severe illness in emergency departments through collaborative machine learning models.

The American journal of emergency medicine Jun 15, 2024
OBJECTIVES: Emergency department (ED) overcrowding presents a global challenge that inhibits prompt care for critically ill patients. Traditional 5-level triage system that heavily rely on the judgment of the triage staff could fail to detect subtle ...
Male Humans Middle Aged Neural Networks, Computer Risk Assessment Triage Female Machine Learning Emergency Service, Hospital Severity of Illness Index Aged ROC Curve Adult Retrospective Studies Taiwan Critical Illness
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Real-Time Sensor-Based Human Activity Recognition for eFitness and eHealth Platforms.

Sensors (Basel, Switzerland) Jun 15, 2024
Human Activity Recognition (HAR) plays an important role in the automation of various tasks related to activity tracking in such areas as healthcare and eldercare (telerehabilitation, telemonitoring), security, ergonomics, entertainment (fitness, spo...
Humans Neural Networks, Computer Algorithms Exercise Telemedicine Human Activities
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