AIMC Topic: Spatial Analysis

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CoSTA: unsupervised convolutional neural network learning for spatial transcriptomics analysis.

BMC bioinformatics Aug 9, 2021
BACKGROUND: The rise of spatial transcriptomics technologies is leading to new insights about how gene regulation happens in a spatial context. Determining which genes are expressed in similar spatial patterns can reveal gene regulatory relationships...
Transcriptome Cluster Analysis Spatial Analysis Neural Networks, Computer
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Machine Learning and Artificial Intelligence-driven Spatial Analysis of the Tumor Immune Microenvironment in Pathology Slides.

European urology focus Aug 3, 2021
A better understanding of the tumor immune microenvironment (TIME) could lead to accurate diagnosis, prognosis, and treatment stratification. Although molecular analyses at the tissue and/or single cell level could reveal the cellular status of the t...
Artificial Intelligence Machine Learning Tumor Microenvironment Humans Neoplasms Spatial Analysis
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Adaptive convolutional neural networks for accelerating magnetic resonance imaging via k-space data interpolation.

Medical image analysis May 16, 2021
Deep learning in k-space has demonstrated great potential for image reconstruction from undersampled k-space data in fast magnetic resonance imaging (MRI). However, existing deep learning-based image reconstruction methods typically apply weight-shar...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Spatial Analysis Humans Neural Networks, Computer Algorithms
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Spatial prediction of human brucellosis (HB) using a GIS-based adaptive neuro-fuzzy inference system (ANFIS).

Acta tropica May 9, 2021
OBJECTIVE: This study pursues three main objectives: 1) exploring the spatial distribution patterns of human brucellosis (HB); 2) identifying parameters affecting the disease spread; and 3) modeling and predicting the spatial distribution of HB cases...
Climate Brucellosis Fuzzy Logic Cluster Analysis Models, Statistical Animals Spatial Analysis Geographic Information Systems Linear Models Incidence Humans Neural Networks, Computer
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A spatially based quantile regression forest model for mapping rural land values.

Journal of environmental management Apr 6, 2021
Rural land valuation plays an important role in the development of land use policies for agricultural purposes. The advance of computational software and machine learning methods has enhanced mass appraisal methodologies for modeling and predicting e...
Environmental Monitoring Spatial Analysis Linear Models Machine Learning Algorithms
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Geographically weighted machine learning model for untangling spatial heterogeneity of type 2 diabetes mellitus (T2D) prevalence in the USA.

Scientific reports Mar 26, 2021
Type 2 diabetes mellitus (T2D) prevalence in the United States varies substantially across spatial and temporal scales, attributable to variations of socioeconomic and lifestyle risk factors. Understanding these variations in risk factors contributio...
Socioeconomic Factors Obesity Spatial Analysis Life Style Geography Sedentary Behavior Humans Prevalence Quality of Life Machine Learning Diabetes Mellitus, Type 2 Exercise Risk Factors United States Diet
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Bilateral attention decoder: A lightweight decoder for real-time semantic segmentation.

Neural networks : the official journal of the International Neural Network Society Jan 30, 2021
The encoder-decoder structure has been introduced into semantic segmentation to improve the spatial accuracy of the network by fusing high- and low-level feature maps. However, recent state-of-the-art encoder-decoder-based methods can hardly attain t...
Machine Learning Spatial Analysis Semantics Pattern Recognition, Automated
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Applying machine learning, text mining, and spatial analysis techniques to develop a highway-railroad grade crossing consolidation model.

Accident; analysis and prevention Jan 22, 2021
The consolidation of Highway-Railroad Grade Crossing (HRGC) is one of the effective approaches to decrease the number of crashes between trains and vehicles. From 2015-2019, there were 57 HRGC crashes at crossings in East Baton Rouge Parish (EBRP), r...
Humans Spatial Analysis Railroads Machine Learning Models, Theoretical Male Accidents, Traffic Data Mining
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Adopting Machine Learning and Spatial Analysis Techniques for Driver Risk Assessment: Insights from a Case Study.

International journal of environmental research and public health Jul 18, 2020
Traffic violations usually caused by aggressive driving behavior are often seen as a primary contributor to traffic crashes. Violations are either caused by an unintentional or deliberate act of drivers that jeopardize the lives of fellow drivers, pe...
Spatial Analysis Pedestrians Accidents, Traffic Automobile Driving Geographic Information Systems China Humans Machine Learning Risk Assessment
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Artificial Neural Network Modeling of Novel Coronavirus (COVID-19) Incidence Rates across the Continental United States.

International journal of environmental research and public health Jun 12, 2020
Prediction of the COVID-19 incidence rate is a matter of global importance, particularly in the United States. As of 4 June 2020, more than 1.8 million confirmed cases and over 108 thousand deaths have been reported in this country. Few studies have ...
United States Algorithms Models, Statistical Machine Learning Spatial Analysis SARS-CoV-2 Risk Factors Incidence Public Health Logistic Models Humans Geographic Information Systems Neural Networks, Computer Pandemics COVID-19 Betacoronavirus Pneumonia, Viral Coronavirus Infections
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