AIMC Topic: Principal Component Analysis

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Cancer Cell Line Classification Using Raman Spectroscopy of Cancer-Derived Exosomes and Machine Learning.

Analytical chemistry
Liquid biopsies are an emerging, noninvasive tool for cancer diagnostics, utilizing biological fluids for molecular profiling. Nevertheless, the current methods often lack the sensitivity and specificity necessary for early detection and real-time mo...

Unsupervised Machine Learning-Based Image Recognition of Raw Infrared Spectra: Toward Chemist-like Chemical Structural Classification and Beyond Numerical Data.

Journal of chemical information and modeling
Recent advances in artificial intelligence have significantly improved spectral data analysis. In this study, we used unsupervised machine learning to classify chemical compounds based on infrared (IR) spectral images, without relying on prior chemic...

Classification of skeletal discrepancies by machine learning based on three-dimensional facial scans.

International journal of oral and maxillofacial surgery
The aim of this study was to use machine learning (ML) to classify sagittal and vertical skeletal discrepancies in three-dimensional (3D) facial scans, as well as to evaluate shape variability. 3D facial scans from 435 pre-orthodontic patients were s...

Exploiting adaptive neuro-fuzzy inference systems for cognitive patterns in multimodal brain signal analysis.

Scientific reports
The analysis of cognitive patterns through brain signals offers critical insights into human cognition, including perception, attention, memory, and decision-making. However, accurately classifying these signals remains a challenge due to their inher...

Single-cell Raman spectroscopy as a novel platform for unveiling the heterogeneity of mesenchymal stem cells.

Talanta
Despite the significant potential of mesenchymal stem cells (MSC) therapy in clinical settings, challenges persist regarding the efficient detection of consistency and uniformity of MSC populations. Raman spectroscopy is a fast, convenient, and nonde...

Advancing the Accuracy of Anti-MRSA Peptide Prediction Through Integrating Multi-Source Protein Language Models.

Interdisciplinary sciences, computational life sciences
The emergence of methicillin-resistant Staphylococcus aureus (MRSA) as a recognized cause of community-acquired and hospital infections has brought about a need for the efficient and accurate identification of peptides with anti-MRSA properties in dr...

Precision soil sampling strategy for the delineation of management zones in olive cultivation using unsupervised machine learning methods.

Scientific reports
Climate change and environmental degradation pose a significant threat to the global community. Soil management is one of the critical factors for achieving climate neutrality, as plants and soils together currently absorb approximately 30% of the CO...

Geographical origin differentiation of Philippine Robusta coffee (C. canephora) using X-ray fluorescence-based elemental profiling with chemometrics and machine learning.

Food chemistry
The increasing demand for authenticity and traceability in high-value crops underscores the need for reliable methods to verify the geographical origin of single-origin coffee and prevent fraud. This study explores a rapid and cost-effective approach...

Prediction of river dissolved oxygen (DO) based on multi-source data and various machine learning coupling models.

PloS one
Too low a concentration of dissolved oxygen (DO) in a river can disrupt the ecological balance, while too high a concentration may lead to eutrophication of the water body and threaten the health of the aquatic environment. Therefore, accurate predic...

Considerations regarding the selection, sampling, extraction, analysis, and modelling of biomarkers in exhaled breath for early lung cancer screening.

Journal of pharmaceutical and biomedical analysis
Lung cancer (LC) is the deadliest cancer due to the lack of efficient screening methods that detect the disease early. This review, covering the years 2011 - 2025, summarizes state-of-the-art LC screening through analysis of volatile organic compound...