AIMC Topic: Discriminant Analysis

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Machine learning classification and biochemical characteristics in the real-time diagnosis of gastric adenocarcinoma using Raman spectroscopy.

Scientific reports Jan 20, 2025
This study aimed to identify biomolecular differences between benign gastric tissues (gastritis/intestinal metaplasia) and gastric adenocarcinoma and to evaluate the diagnostic power of Raman spectroscopy-based machine learning in gastric adenocarcin...
Spectrum Analysis, Raman Adenocarcinoma Principal Component Analysis Discriminant Analysis Stomach Neoplasms Male Middle Aged Humans Aged Aged, 80 and over Machine Learning Female
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Classification of NSCLC subtypes using lung microbiome from resected tissue based on machine learning methods.

NPJ systems biology and applications Jan 17, 2025
Classification of adenocarcinoma (AC) and squamous cell carcinoma (SCC) poses significant challenges for cytopathologists, often necessitating clinical tests and biopsies that delay treatment initiation. To address this, we developed a machine learni...
Carcinoma, Squamous Cell Lung Lung Neoplasms Carcinoma, Non-Small-Cell Lung Humans Machine Learning Algorithms Discriminant Analysis Microbiota
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High-throughput, rapid, and non-destructive detection of common foodborne pathogens via hyperspectral imaging coupled with deep neural networks and support vector machines.

Food research international (Ottawa, Ont.) Jan 7, 2025
Foodborne pathogens such as Bacillus cereus, Staphylococcus aureus, and Escherichia coli are major causes of gastrointestinal diseases worldwide and frequently contaminate dairy products. Compared to nucleic acid detection and MALDI-TOF MS, hyperspec...
Hyperspectral Imaging Bacillus cereus Principal Component Analysis Discriminant Analysis High-Throughput Screening Assays Food Contamination Food Microbiology Foodborne Diseases Neural Networks, Computer Escherichia coli Staphylococcus aureus Deep Learning Support Vector Machine
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Rapid detection of drug abuse via tear analysis using surface enhanced Raman spectroscopy and machine learning.

Scientific reports Jan 7, 2025
With the growing global challenge of drug abuse, there is an urgent need for rapid, accurate, and cost-effective drug detection methods. This study introduces an innovative approach to drug abuse screening by quickly detecting ephedrine (EPH) in tear...
Algorithms Animals Male Rats Spectrum Analysis, Raman Machine Learning Discriminant Analysis Rats, Sprague-Dawley Tears Substance-Related Disorders Tandem Mass Spectrometry Substance Abuse Detection
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Trace detection of antibiotics in wastewater using tunable core-shell nanoparticles SERS substrate combined with machine learning algorithms.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jan 5, 2025
Surface-enhanced Raman scattering (SERS) show great potential for rapid and highly sensitive detection of trace amounts of contamination from the environment in the surface aquatic ecosystem. The widespread use of antibiotics has resulted in serious ...
Silver Ciprofloxacin Spectrum Analysis, Raman Support Vector Machine Water Pollutants, Chemical Wastewater Machine Learning Least-Squares Analysis Principal Component Analysis Algorithms Anti-Bacterial Agents Metal Nanoparticles Discriminant Analysis
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Identification of Phosphodiesterase type 5 inhibitors (PDE5is) analogues using surface-enhanced Raman scattering and machine learning algorithm.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Dec 27, 2024
Phosphodiesterase type 5 inhibitors (PDE5is), primarily used for the treatment of erectile dysfunction, have been severely misused in recent years, posing a threat to public health and safety. This study developed a method that combines Surface-enhan...
Spectrum Analysis, Raman Gold Humans Discriminant Analysis Metal Nanoparticles Support Vector Machine Machine Learning Least-Squares Analysis Phosphodiesterase 5 Inhibitors Principal Component Analysis Algorithms
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Rapid detection of microplastics in chicken feed based on near infrared spectroscopy and machine learning algorithm.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Dec 20, 2024
The main objective of this study was to evaluate the potential of near infrared (NIR) spectroscopy and machine learning in detecting microplastics (MPs) in chicken feed. The application of machine learning techniques in building optimal classificatio...
Support Vector Machine Food Contamination Machine Learning Principal Component Analysis Least-Squares Analysis Algorithms Animals Discriminant Analysis Spectroscopy, Near-Infrared Animal Feed Chickens Microplastics
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A rapid, non-destructive, and accurate method for identifying citrus granulation using Raman spectroscopy and machine learning.

Journal of food science Dec 10, 2024
Citrus fruits are widely consumed for their nutritional value and taste; however, juice sac granulation during fruit storage poses a significant challenge to the citrus industry. This study used Raman spectroscopy coupled with machine learning algori...
Machine Learning Algorithms Spectrum Analysis, Raman Fruit and Vegetable Juices Principal Component Analysis Citrus Least-Squares Analysis Discriminant Analysis Fruit
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Using three-dimensional fluorescence spectroscopy and machine learning for rapid detection of adulteration in camellia oil.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Dec 3, 2024
Camellia oil had been widely utilized in the realms of cooking, healthcare, and beauty. Nevertheless, merchants frequently adulterated pure camellia oil with low-priced oils to cut costs. This study was aimed at identifying the authenticity of camell...
Machine Learning Support Vector Machine Food Contamination Camellia Least-Squares Analysis Neural Networks, Computer Plant Oils Discriminant Analysis Spectrometry, Fluorescence
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Brain Network Classification for Accurate Detection of Alzheimer's Disease via Manifold Harmonic Discriminant Analysis.

IEEE transactions on neural networks and learning systems Dec 2, 2024
Mounting evidence shows that Alzheimer's disease (AD) manifests the dysfunction of the brain network much earlier before the onset of clinical symptoms, making its early diagnosis possible. Current brain network analyses treat high-dimensional networ...
Alzheimer Disease Nerve Net Algorithms Brain Aged Humans Discriminant Analysis Neural Networks, Computer
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