Common spatial pattern
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Cancer is a significant public health concern and the second leading cause of death. This study aims to visualize spatial patterns of top common cancer types and identify high-risk and low-risk counties for these cancers in Iran from 2014 to 2017.
14p vikoch 27-06-2024 1 1 Download
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The paper "A novel approach of neural networks and USLE in smart soil erosion modeling, case study in Southern coastal of Viet Nam" adopted one of the neural networks - the Long ShortTerm Memory (LSTM) to analyze temporal variations in erosion patterns over time, aiding in understanding erosion dynamics. Furthermore, another common soil erosion model - the Universal Soil Loss Equation (USLE) was investigated to predict annual soil loss. Our data were extracted from remotely sensed data (DEM - Digital Elevation Model and MODIS) and vector data of the study area.
11p tukhauquantuong1011 22-04-2024 6 2 Download
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A stronger spatial clustering of cancer burden indicates stronger environmental and human behavioral effects. However, which common cancers in China have stronger spatial clustering and knowledge gaps regarding the environmental and human behavioral efects have yet to be investigated.
12p viferrari 28-11-2022 6 2 Download
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Spatial transcriptomic studies are becoming increasingly common and large, posing important statistical and computational challenges for many analytic tasks. Here, we present SPARK-X, a non-parametric method for rapid and effective detection of spatially expressed genes in large spatial transcriptomic studies.
25p viarchimedes 26-01-2022 13 0 Download
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Common spatial pattern (CSP) has been an effective technique for feature extraction in electroencephalography (EEG) based brain computer interfaces (BCIs). However, motor imagery EEG signal feature extraction using CSP generally depends on the selection of the frequency bands to a great extent.
13p viconnecticut2711 29-10-2020 9 1 Download
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High-throughput expression profiling experiments with ordered conditions (e.g. time-course or spatial-course) are becoming more common for studying detailed differentiation processes or spatial patterns. Identifying dynamic changes at both the individual gene and whole transcriptome level can provide important insights about genes, pathways, and critical time points.
10p viconnecticut2711 28-10-2020 14 0 Download