AIMC Topic: Discriminant Analysis
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Rapid classification of Camellia seed varieties and non-destructive high-throughput quantitative analysis of fatty acids based on non-targeted fingerprint spectroscopy combined with chemometrics.
Food chemistry
Feb 1, 2025
Camellia oil is a high-quality vegetable oil rich in unsaturated fatty acids (FAs), with quality standardization challenged by the diversity of Camellia seed varieties. This study compared spectroscopy techniques (Near-Infrared [NIR] vs Mid-Infrared ...
A holistic strategy for the in-depth discrimination and authentication of 16 citrus herbs and associated commercial products based on machine learning techniques and non-targeted metabolomics.
Journal of chromatography. A
Feb 1, 2025
Citrus-derived raw medicinal materials are frequently used for health care, flavoring, and therapeutic purposes. However, Due to similarities in origin or appearance, citrus herbs are often misused in the market, necessitating effective differentiati...
Sexual dimorphism of the humerus bones in a French sample: comparison of several statistical models including machine learning models.
International journal of legal medicine
Jan 25, 2025
Sex estimation is an important part of skeletal analysis and forensic identification. Traditionally pelvic traits are utilized for accurate sex estimation. However, the long bones, especially humerus, have been proved to be as effective for determine...
Automated mold defects classification in paintings: A comparison of machine learning and rule-based techniques.
PloS one
Jan 24, 2025
Mold defects pose a significant risk to the preservation of valuable fine art paintings, typically arising from fungal growth in humid environments. This paper presents a novel approach for detecting and categorizing mold defects in fine art painting...
Advancing DNA Structural Analysis: A SERS Approach Free from Citrate Interference Combined with Machine Learning.
The journal of physical chemistry letters
Jan 23, 2025
Surface-enhanced Raman spectroscopy (SERS) has become an indispensable tool for biomolecular analysis, yet the detection of DNA signals remains hindered by spectral interference from citrate ions, which overlap with key DNA features. This study intro...
Prediction of coffee traits by artificial neural networks and laser-assisted rapid evaporative ionization mass spectrometry.
Food research international (Ottawa, Ont.)
Jan 23, 2025
BACKGROUND: Coffee is an important commodity in the worldwide economy and smart technologies are important for accurate quality control and consumer-oriented product development. Sensory perception is probably the most important information since it ...
Hyoid bone-based sex discrimination among Egyptians using a multidetector computed tomography: discriminant function analysis, meta-analysis, and artificial intelligence-assisted study.
Scientific reports
Jan 21, 2025
The hyoid bone has been identified as sexually dimorphic in various populations. The current study is a forerunner analysis that used three-dimensional multidetector computed tomography (3D MDCT) images of the hyoid bone to examine sexual dimorphism ...
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...
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...
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...
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