AIMC Topic: Spectrum Analysis, Raman

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Vibrational spectroscopy of body fluids combined with machine learning for the early diagnosis of cystic echinococcosis.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Mar 17, 2025
Cystic echinococcosis (CE) is a globally prevalent zoonotic parasitic disease. Due to the covert symptoms and the inadequacies of screening technologies, accurate early diagnosis is crucial. This study explores the feasibility of employing body fluid...
Machine Learning Biomarkers Mice Spectrum Analysis, Raman Animals Echinococcosis Support Vector Machine Spectroscopy, Fourier Transform Infrared Body Fluids Early Diagnosis
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Advanced SERSome-based artificial-intelligence technology for identifying medicinal and edible homologs.

Talanta Mar 12, 2025
Medicinal and edible homologs (MEHs) offer significant preventive and therapeutic benefits for various diseases and health functions. However, the widespread application of MEHs faces significant challenges, particularly in quality control and rapid ...
Metal Nanoparticles Silver Calcium Deep Learning Spectrum Analysis, Raman Humans Artificial Intelligence
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Identification of Fusarium sambucinum species complex by surface-enhanced Raman spectroscopy and XGBoost algorithm.

Food chemistry Mar 12, 2025
Rapid and reliable identification of Fusarium fungi is crucial, due to their role in food spoilage and potential toxicity. Traditional identification methods are often time-consuming and resource-intensive. This study explores the use of surface-enha...
Spectrum Analysis, Raman Hordeum Fusarium Boosting Machine Learning Algorithms
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Comprehensive Raman spectroscopy analysis for differentiating toxic cyanobacteria through multichannel 1D-CNNs and SHAP-based explainability.

Talanta Mar 7, 2025
Cyanobacterial blooms pose significant environmental and public health risks due to the production of toxins that contaminate water sources and disrupt aquatic ecosystems. Rapid and accurate identification of cyanobacterial species is crucial for eff...
Spectrum Analysis, Raman Harmful Algal Bloom Cyanobacteria Deep Learning Neural Networks, Computer
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An ultra-sensitive, intelligent platform for food safety monitoring: Label-free detection of illegal additives using self-assembled SERS substrates and machine learning.

Food chemistry Mar 7, 2025
To overcome the limitations of SERS in food safety monitoring, particularly significant interference from citrate ions, this study introduces an intelligent SERS-based platform for food safety monitoring. The platform utilizes sodium borohydride to a...
Spectrum Analysis, Raman Food Contamination Machine Learning Silver Food Additives Food Safety Metal Nanoparticles Limit of Detection
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Measuring the severity of knee osteoarthritis with an aberration-free fast line scanning Raman imaging system.

Analytica chimica acta Mar 5, 2025
Osteoarthritis (OA) is a major cause of disability worldwide, with symptoms like joint pain, limited functionality, and decreased quality of life, potentially leading to deformity and irreversible damage. Chemical changes in joint tissues precede ima...
Osteoarthritis, Knee Algorithms Severity of Illness Index Humans Spectrum Analysis, Raman Deep Learning Signal-To-Noise Ratio
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Comprehensive Raman Fingerprinting and Machine Learning-Based Classification of 14 Pesticides Using a 785 nm Custom Raman Instrument.

Biosensors Mar 5, 2025
Raman spectroscopy enables fast, label-free, qualitative, and quantitative observation of the physical and chemical properties of various substances. Here, we present a 785 nm custom-built Raman spectroscopy instrument designed for sensing applicatio...
Spectrum Analysis, Raman Machine Learning Pesticides
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A Surface-Enhanced Raman Spectroscopy Platform Integrating Dual Signal Enhancement and Machine Learning for Rapid Detection of Veterinary Drug Residues in Meat Products.

ACS applied materials & interfaces Mar 2, 2025
The detection and quantification of veterinary drug residues in meat remain a significant challenge due to the complex background interference inherent to the meat matrix, which compromises the stability and accuracy of spectroscopic analysis. This s...
Spectrum Analysis, Raman Food Contamination Metal Nanoparticles Machine Learning Animals Veterinary Drugs Meat Products Drug Residues
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Predicting oleogels properties using non-invasive spectroscopic techniques and machine learning.

Food research international (Ottawa, Ont.) Feb 26, 2025
Oleogelators are considered food additives that require approval from regulatory authorities. Therefore, classifying these ingredients that may have characteristics (e.g., waxiness), cost and origin (e.g., animal or vegetable) is crucial to ensure co...
Waxes Sunflower Oil Cellulose Food Additives Organic Chemicals Least-Squares Analysis Principal Component Analysis Soybean Oil Spectrum Analysis, Raman Fatty Acids, Nonesterified Machine Learning Spectroscopy, Near-Infrared
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Machine learning enabled protein secondary structure characterization using drop-coating deposition Raman spectroscopy.

Journal of pharmaceutical and biomedical analysis Feb 25, 2025
Protein structure characterization is critical for therapeutic protein drug development and production. Drop-coating deposition Raman (DCDR) spectroscopy offers rapid and cost-effective acquisition of vibrational spectral data characteristic of prote...
Spectrum Analysis, Raman Protein Structure, Secondary Machine Learning Proteins Algorithms Least-Squares Analysis
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