AIMC Topic: Multivariate Analysis
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Multivariate and Machine Learning-Derived Virtual Staining and Biochemical Quantification of Cancer Cells through Raman Hyperspectral Imaging.
Analytical chemistry
Jun 11, 2025
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
Jun 10, 2025
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...
Dual-energy CT combined with histogram parameters in the assessment of perineural invasion in colorectal cancer.
International journal of colorectal disease
May 27, 2025
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
May 26, 2025
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
May 23, 2025
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.
Dual-stream interactive networks with pearson-mask awareness for multivariate time series forecasting.
Neural networks : the official journal of the International Neural Network Society
May 17, 2025
Multivariate time series forecasting (MTSF) aims to predict time series data containing multiple variates, which requires the consideration of both intra-series temporal trends and inter-series interactions. Benefiting from the success of Transformer...
Defining the biomarkers in anti-MRSA fractions of soil Streptomycetes by multivariate analysis.
Antonie van Leeuwenhoek
May 10, 2025
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...
Construction of enhanced MRI-based radiomics models using machine learning algorithms for non-invasive prediction of IL7R expression in high-grade gliomas and its prognostic value in clinical practice.
Journal of translational medicine
Mar 31, 2025
BACKGROUND: High-grade gliomas are among the most aggressive and deadly brain tumors, highlighting the critical need for improved prognostic markers and predictive models. Recent studies have identified the expression of IL7R as a significant risk fa...
Receptors, Interleukin-7
Interleukin-7 Receptor alpha Subunit
Radiomics
Brain Neoplasms
Neoplasm Grading
ROC Curve
Female
Humans
Male
Glioma
Proportional Hazards Models
Aged
Machine Learning
Middle Aged
Multivariate Analysis
Adult
Algorithms
Support Vector Machine
Kaplan-Meier Estimate
Magnetic Resonance Imaging
Prognosis
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...
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