AIMC Topic: Spatio-Temporal Analysis

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Spatio-temporal epidemic forecasting using mobility data with LSTM networks and attention mechanism.

Scientific reports Mar 20, 2025
The outbreak of infectious diseases can have profound impacts on socio-economic balances globally. Accurate short-term forecasting of infectious diseases is crucial for policymakers and healthcare systems. This study proposes a novel deep learning ap...
Japan Epidemics Hospitalization Spatio-Temporal Analysis Deep Learning Humans COVID-19 Forecasting SARS-CoV-2
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Uncovering water conservation patterns in semi-arid regions through hydrological simulation and deep learning.

PloS one Mar 20, 2025
Under the increasing pressure of global climate change, water conservation (WC) in semi-arid regions is experiencing unprecedented levels of stress. WC involves complex, nonlinear interactions among ecosystem components like vegetation, soil structur...
Ecosystem Climate Change Computer Simulation Spatio-Temporal Analysis Conservation of Water Resources Desert Climate Droughts Deep Learning Hydrology
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Dynamic Graph Representation Learning for Spatio-Temporal Neuroimaging Analysis.

IEEE transactions on cybernetics Mar 6, 2025
Neuroimaging analysis aims to reveal the information-processing mechanisms of the human brain in a noninvasive manner. In the past, graph neural networks (GNNs) have shown promise in capturing the non-Euclidean structure of brain networks. However, e...
Humans Spatio-Temporal Analysis Image Processing, Computer-Assisted Neuroimaging Neural Networks, Computer Algorithms Brain
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Enhanced U-Net for Infant Brain MRI Segmentation: A (2+1)D Convolutional Approach.

Sensors (Basel, Switzerland) Feb 28, 2025
BACKGROUND: Infant brain tissue segmentation from MRI data is a critical task in medical imaging, particularly challenging due to the evolving nature of tissue contrasts in the early months of life. The difficulty increases as gray matter (GM) and wh...
Humans Brain Infant Spatio-Temporal Analysis White Matter Deep Learning Convolutional Neural Networks Cerebrospinal Fluid Datasets as Topic Gray Matter Imaging, Three-Dimensional Image Processing, Computer-Assisted Magnetic Resonance Imaging
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High-resolution spatio-temporal estimation of street-level air pollution using mobile monitoring and machine learning.

Journal of environmental management Feb 21, 2025
High spatio-temporal resolution street-level air pollution (SLAP) estimation is essential for urban air quality management, yet traditional methods face significant challenges in capturing the detailed spatial and temporal variability of pollution. M...
Air Pollution Particulate Matter Machine Learning Cities Spatio-Temporal Analysis Environmental Monitoring Air Pollutants
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Spatio-temporal transformers for decoding neural movement control.

Journal of neural engineering Feb 4, 2025
. Deep learning tools applied to high-resolution neurophysiological data have significantly progressed, offering enhanced decoding, real-time processing, and readability for practical applications. However, the design of artificial neural networks to...
Neural Networks, Computer Animals Male Motor Cortex Neurons Macaca mulatta Psychomotor Performance Movement Spatio-Temporal Analysis Models, Neurological Action Potentials
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Deep learning initialized compressed sensing (Deli-CS) in volumetric spatio-temporal subspace reconstruction.

Magma (New York, N.Y.) Feb 1, 2025
OBJECT: Spatio-temporal MRI methods offer rapid whole-brain multi-parametric mapping, yet they are often hindered by prolonged reconstruction times or prohibitively burdensome hardware requirements. The aim of this project is to reduce reconstruction...
Imaging, Three-Dimensional Image Processing, Computer-Assisted Magnetic Resonance Imaging Brain Spatio-Temporal Analysis Deep Learning Brain Mapping Phantoms, Imaging Data Compression Humans Algorithms
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A novel graph neural network based approach for influenza-like illness nowcasting: exploring the interplay of temporal, geographical, and functional spatial features.

BMC public health Feb 1, 2025
BACKGROUND: Accurate and timely monitoring of influenza prevalence is essential for effective healthcare interventions. This study proposes a graph neural network (GNN)-based method to address the issue of cross-regional connectivity in predicting in...
Disease Outbreaks Spatio-Temporal Analysis Influenza, Human Graph Neural Networks Humans Neural Networks, Computer Forecasting
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Modelling the seasonal dynamics of Aedes albopictus populations using a spatio-temporal stacked machine learning model.

Scientific reports Jan 30, 2025
Various modelling techniques are available to understand the temporal and spatial variations of the phenology of species. Scientists often rely on correlative models, which establish a statistical relationship between a response variable (such as spe...
Seasons Aedes Mosquito Vectors Spatio-Temporal Analysis Machine Learning Population Dynamics Animals Models, Biological
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Spatiotemporal variation in biomass abundance of different algal species in Lake Hulun using machine learning and Sentinel-3 images.

Scientific reports Jan 21, 2025
Climate change and human activities affect the biomass of different algal and the succession of dominant species. In the past, phytoplankton phyla inversion has been focused on oceanic and continental shelf waters, while phytoplankton phyla inversion...
Climate Change Chlorophyta Satellite Imagery Remote Sensing Technology Lakes Machine Learning Phytoplankton Spatio-Temporal Analysis Cyanobacteria Environmental Monitoring Biomass
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