AIMC Topic: Multivariate Analysis

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PRformer: Pyramidal recurrent transformer for multivariate time series forecasting.

Neural networks : the official journal of the International Neural Network Society
The self-attention mechanism in Transformer architecture, invariant to sequence order, necessitates positional embeddings to encode temporal order in time series prediction. We argue that this reliance on positional embeddings restricts the Transform...

Advancing freshness classification of freshly squeezed fruit juice via integrated multivariate analysis and machine learning approaches.

Food chemistry
In this study, multivariate analysis (MVA) and machine learning (ML), combined with UHPLC-HRMS, were used to evaluate the freshness of apples for juice production based on the analysis of freshly squeezed apple juice. A total of eight stages of apple...

A study on time-series prediction and analysis of acidity of Daqu based on multivariate data fusion and KNN-Attention-LSTM-XGBoost modeling.

Bioprocess and biosystems engineering
Daqu is a traditional Chinese brewing ingredient that serves dual functions of saccharification and fermentation during the brewing process. The acidity content during the Daqu fermentation process directly affects the quality of the Daqu. Traditiona...

Multivariate and Machine Learning-Derived Virtual Staining and Biochemical Quantification of Cancer Cells through Raman Hyperspectral Imaging.

Analytical chemistry
Advances in virtual staining and spatial omics have revolutionized our ability to explore cellular architecture and molecular composition with unprecedented detail. Virtual staining techniques, which rely on computational algorithms to map molecular ...

Multivariate brain morphological patterns across mood disorders: key roles of frontotemporal and cerebellar areas.

BMJ mental health
BACKGROUND: Differentiating major depressive disorder (MDD) from bipolar disorder (BD) remains a significant clinical challenge, as both disorders exhibit overlapping symptoms but require distinct treatment approaches. Advances in voxel-based morphom...

A Scalable Deep Learning Approach for Real-Time Multivariate Monitoring of Biopharmaceutical Processes With No Prior Product-Specific History.

Biotechnology and bioengineering
Real-time multivariate statistical process monitoring (RT-MSPM) is essential to monitor health of bio-pharmaceutical processes and detect anomalies and faults early in the process. RT-MSPM methods are commonly used to monitor cell culture process ope...

Dual-energy CT combined with histogram parameters in the assessment of perineural invasion in colorectal cancer.

International journal of colorectal disease
PURPOSE: The purpose is to evaluate the predictive value of dual-energy CT (DECT) combined with histogram parameters and a clinical prediction model for perineural invasion (PNI) in colorectal cancer (CRC).

Easy and Fast Discrimination of Female Sand Flies from Species with Infrared Spectroscopy and Multivariate Analysis.

Analytical chemistry
Accurate identification of sandfly species is critical for controlling and preventing the spread of visceral leishmaniasis, a major public health concern in Latin America. Morphological similarities between female and present a significant challeng...

Leveraging Digital Twins for Stratification of Patients with Breast Cancer and Treatment Optimization in Geriatric Oncology: Multivariate Clustering Analysis.

JMIR cancer
BACKGROUND: Defining optimal adjuvant therapeutic strategies for older adult patients with breast cancer remains a challenge, given that this population is often overlooked and underserved in clinical research and decision-making tools.

Defining the biomarkers in anti-MRSA fractions of soil Streptomycetes by multivariate analysis.

Antonie van Leeuwenhoek
Methicillin-resistant Staphylococcus aureus (MRSA) is one of the most alarming antibiotic-resistant pathogens causing nosocomial and community-acquired infections. Actinomycetes, particularly Streptomycetes, have historically been a major source of n...