AIMC Topic: Spatio-Temporal Analysis
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Managing spatio-temporal heterogeneity of susceptibles by embedding it into an homogeneous model: A mechanistic and deep learning study.
PLoS computational biology
Sep 30, 2024
Accurate prediction of epidemics is pivotal for making well-informed decisions for the control of infectious diseases, but addressing heterogeneity in the system poses a challenge. In this study, we propose a novel modelling framework integrating the...
Classifying eutrophication spatio-temporal dynamics in river systems using deep learning technique.
The Science of the total environment
Sep 29, 2024
Eutrophication is a major cause of water quality degradation in South Korea, owing to severe algal blooms. To manage eutrophication, the South Korean government provided the Trophic State Index (TSIko), which was revised according to Carlson's TSI. T...
SELFNet: Denoising Shear Wave Elastography Using Spatial-temporal Fourier Feature Networks.
Ultrasound in medicine & biology
Sep 23, 2024
OBJECTIVE: Ultrasound-based shear wave elastography offers estimation of tissue stiffness through analysis of the propagation of a shear wave induced by a stimulus. Displacement or velocity fields during the process can contain noise as a result of t...
Spatiotemporal modelling of airborne birch and grass pollen concentration across Switzerland: A comparison of statistical, machine learning and ensemble methods.
Environmental research
Sep 20, 2024
BACKGROUND: Statistical and machine learning models are commonly used to estimate spatial and temporal variability in exposure to environmental stressors, supporting epidemiological studies. We aimed to compare the performances, strengths and limitat...
A Novel Method to Identify Mild Cognitive Impairment Using Dynamic Spatio-Temporal Graph Neural Network.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 16, 2024
Resting-state functional magnetic resonance imaging (rs-fMRI) has been widely used in the identification of mild cognitive impairment (MCI) research, MCI patients are relatively at a higher risk of progression to Alzheimer's disease (AD). However, al...
Geospatial and Temporal Analysis of Avian Influenza Risk in Thailand: A GIS-Based Multi-Criteria Decision Analysis Approach for Enhanced Surveillance and Control.
Transboundary and emerging diseases
Sep 13, 2024
Avian influenza (AI) is a viral infection that profoundly affects global poultry production. This study aimed to identify the spatial and temporal factors associated with AI in Thailand, using a geographic information system (GIS)-based multi-criteri...
Multimodal Social Sensing for the Spatio-Temporal Evolution and Assessment of Nature Disasters.
Sensors (Basel, Switzerland)
Sep 11, 2024
Social sensing, using humans as sensors to collect disaster data, has emerged as a timely, cost-effective, and reliable data source. However, research has focused on the textual data. With advances in information technology, multimodal data such as i...
A new attention-based CNN_GRU model for spatial-temporal PM prediction.
Environmental science and pollution research international
Aug 23, 2024
Accurately predicting the spatial-temporal distribution of PM is challenging due to missing data and selecting an appropriate modeling method. Effective imputation of missing data must consider the relationships between variables while preserving the...
Groundwater health risk assessment and its temporal and spatial evolution based on trapezoidal fuzzy number-Monte Carlo stochastic simulation: A case study in western Jilin province.
Ecotoxicology and environmental safety
Jul 17, 2024
The United States Environmental Protection Agency (USEPA) Four-step-Method (FSM) is a straightforward and extensively utilized tool for evaluating regional health risks, However, the complex and heterogeneous groundwater environment system causes gre...
A spatio-temporal graph convolutional network for ultrasound echocardiographic landmark detection.
Medical image analysis
Jul 10, 2024
Landmark detection is a crucial task in medical image analysis, with applications across various fields. However, current methods struggle to accurately locate landmarks in medical images with blurred tissue boundaries due to low image quality. In pa...
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