AIMC Topic: Multivariate Analysis
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Multivariate Classification of Adolescent Major Depressive Disorder Using Whole-brain Functional Connectivity.
Academic radiology
Mar 29, 2025
RATIONALE AND OBJECTIVES: Adolescent major depressive disorder (MDD) is a serious mental health condition that has been linked to abnormal functional connectivity (FC) patterns within the brain. However, whether FC could be used as a potential biomar...
Automated deep learning-based assessment of tumour-infiltrating lymphocyte density determines prognosis in colorectal cancer.
Journal of translational medicine
Mar 10, 2025
BACKGROUND: The presence of tumour-infiltrating lymphocytes (TILs) is a well-established prognostic biomarker across multiple cancer types, with higher TIL counts being associated with lower recurrence rates and improved patient survival. We aimed to...
Machine Learning-Aided Intelligent Monitoring of Multivariate miRNA Biomarkers Using Bipolar Self-powered Sensors.
ACS nano
Feb 26, 2025
Breast cancer has become the most prevalent form of cancer among women on a global scale. The early and timely diagnosis of breast cancer is of the utmost importance for improving the survival rate of patients with this disease. The occurrence of bre...
Dynamic graph-based bilateral recurrent imputation network for multivariate time series.
Neural networks : the official journal of the International Neural Network Society
Feb 19, 2025
Multivariate time series imputation using graph neural networks (GNNs) has gained significant attention, where the variables and their correlations are depicted as the graph nodes and edges, offering a structured way to understand the intricacies of ...
Hyperbolic multivariate feature learning in higher-order heterogeneous networks for drug-disease prediction.
Artificial intelligence in medicine
Feb 19, 2025
New drug discovery has always been a costly, time-consuming process with a high failure rate. Repurposing existing drugs offers a valuable alternative and reduces the risks associated with developing new drugs. Various experimental methods have been ...
Classification and predictive leaching risk assessment of construction and demolition waste using multivariate statistical and machine learning analyses.
Waste management (New York, N.Y.)
Feb 19, 2025
Managing construction and demolition waste (CDW) poses serious concerns regarding landfilling and recycling because of the potential release of hazardous elements after leaching. Ceramic materials such as bricks, tiles, and porcelain account for more...
Unveiling the potential of Brachiaria ruziziensis: Comparative analysis of multivariate and machine learning models for biomass and NPK prediction using Vis-NIR-SWIR spectroscopy.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Feb 18, 2025
This study investigated the development and validation of predictive models for estimating foliar nitrogen (N), phosphorus (P), and potassium (K) contents, along with shoot dry mass (SDM) of Brachiaria ruziziensis L. The approach utilized Vis-NIR-SWI...
Exploring hyperelastic material model discovery for human brain cortex: Multivariate analysis vs. artificial neural network approaches.
Journal of the mechanical behavior of biomedical materials
Feb 10, 2025
The human brain, characterized by its intricate architecture, exhibits complex mechanical properties that underpin its critical functional capabilities. Traditional computational methods, such as finite element analysis, have been instrumental in unc...
Rapid discrimination of different primary processing Arabica coffee beans using FT-IR and machine learning.
Food research international (Ottawa, Ont.)
Feb 10, 2025
In this study, fourier transform infrared spectroscopy (FT-IR) analysis was combined with machine learning, while various analytical techniques such as colorimetry, low-field nuclear magnetic resonance spectroscopy, scanning electron microscope, two-...
DGMSCL: A dynamic graph mixed supervised contrastive learning approach for class imbalanced multivariate time series classification.
Neural networks : the official journal of the International Neural Network Society
Jan 17, 2025
In the Imbalanced Multivariate Time Series Classification (ImMTSC) task, minority-class instances typically correspond to critical events, such as system faults in power grids or abnormal health occurrences in medical monitoring. Despite being rare a...
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