AIMC Topic: Multivariate Analysis
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Correlation Fuzzy measure of multivariate time series for signature recognition.
PloS one
Oct 7, 2024
Distinguishing different time series, which is determinant or stochastic, is an important task in signal processing. In this work, a correlation measure constructs Correlation Fuzzy Entropy (CFE) to discriminate Chaos and stochastic series. It can be...
Multi-scale convolution enhanced transformer for multivariate long-term time series forecasting.
Neural networks : the official journal of the International Neural Network Society
Sep 23, 2024
In data analysis and forecasting, particularly for multivariate long-term time series, challenges persist. The Transformer model in deep learning methods has shown significant potential in time series forecasting. The Transformer model's dot-product ...
A novel model for predicting postoperative liver metastasis in R0 resected pancreatic neuroendocrine tumors: integrating computational pathology and deep learning-radiomics.
Journal of translational medicine
Aug 14, 2024
BACKGROUND: Postoperative liver metastasis significantly impacts the prognosis of pancreatic neuroendocrine tumor (panNET) patients after R0 resection. Combining computational pathology and deep learning radiomics can enhance the detection of postope...
Polygonati Rhizoma varieties and origins traceability based on multivariate data fusion combined with an artificial intelligence classification algorithm.
Food chemistry
Jul 5, 2024
This study collected multidimensional feature data such as spectra, texture, and component contents of Polygonati Rhizoma from different origins and varieties (Polygonatum kingianum Coll. et Hemsl from Yunnan and Guizhou; Polygonatum cyrtonema Hua fr...
Multivariate modeling and prediction of cerebral physiology in acute traumatic neural injury: A scoping review.
Computers in biology and medicine
Jun 20, 2024
Traumatic brain injury (TBI) poses a significant global public health challenge necessitating a profound understanding of cerebral physiology. The dynamic nature of TBI demands sophisticated methodologies for modeling and predicting cerebral signals ...
Anomaly detection in multivariate time series data using deep ensemble models.
PloS one
Jun 6, 2024
Anomaly detection in time series data is essential for fraud detection and intrusion monitoring applications. However, it poses challenges due to data complexity and high dimensionality. Industrial applications struggle to process high-dimensional, c...
Classifying Routine Clinical Electroencephalograms With Multivariate Iterative Filtering and Convolutional Neural Networks.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
May 31, 2024
Electroencephalogram (EEG) is widely used in basic and clinical neuroscience to explore neural states in various populations, and classifying these EEG recordings is a fundamental challenge. While machine learning shows promising results in classifyi...
A robust multi-scale feature extraction framework with dual memory module for multivariate time series anomaly detection.
Neural networks : the official journal of the International Neural Network Society
May 20, 2024
Although existing reconstruction-based multivariate time series anomaly detection (MTSAD) methods have shown advanced performance, most assume the training data is clean. When faced with noise or contamination in training data, they can also reconstr...
Method for Incomplete and Imbalanced Data Based on Multivariate Imputation by Chained Equations and Ensemble Learning.
IEEE journal of biomedical and health informatics
May 6, 2024
The classification analysis of incomplete and imbalanced data is still a challenging task since these issues could negatively impact the training of classifiers, which were also found in our study on the physical fitness assessments of patients. And ...
Multivariate analysis of the kinematics of an upper limb rehabilitation robot.
Acta of bioengineering and biomechanics
Apr 22, 2024
The purpose of this work is to present a multivariate analysis of the kinematics of an upper limb rehabilitation robot. Comparing multiple concepts of kinematic chains makes it possible to identify advantages and disadvantages and, as a consequence,...
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