AIMC Topic: Spectrum Analysis, Raman

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Transfer learning from inorganic materials to ivory detection.

Scientific reports May 3, 2025
This paper describes the automatic identification of ivory using Raman spectroscopy data and deep neural network (DNN) models pre-trained on open-source data from inorganic minerals. The proposed approach uses transfer learning (TL) from foundation m...
Animals Spectrum Analysis, Raman Elephants Mammoths Minerals Neural Networks, Computer Machine Learning
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Label-free rapid diagnosis of jaw osteonecrosis via the intersection of Raman spectroscopy and deep learning.

Bone May 2, 2025
OBJECTIVES: To establish a precise and efficient diagnostic framework for distinguishing medication-related osteonecrosis of the jaw, radiation-induced osteonecrosis of the jaw, and normal bone tissue, thus enhancing clinical decision-making and enab...
Male Middle Aged Humans Female Spectrum Analysis, Raman Principal Component Analysis Discriminant Analysis Deep Learning ROC Curve
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High-Precision Intelligent Diagnosis of Pancreatic Cancer: Flowing Diffuseness from Single to Whole.

Analytical chemistry Apr 29, 2025
Raman spectroscopy, as a label-free optical technique, provides a unique solution for tissue diagnosis. However, due to the limitation of point-by-point acquisition mode and multivariate statistical analysis methods, conventional methods pose a major...
Spectrum Analysis, Raman Pancreatic Neoplasms Humans Deep Learning
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Spectroscopic techniques combined with chemometrics for rapid detection of food adulteration: Applications, perspectives, and challenges.

Food research international (Ottawa, Ont.) Apr 20, 2025
Food adulteration is an important threat to food safety and can be difficult to detect. Some analytical methods are complex and difficult to meet the needs of large numbers of samples. In this study, we introduced the application of six spectroscopic...
Food Analysis Spectrum Analysis Spectroscopy, Fourier Transform Infrared Chemometrics Food Contamination Spectroscopy, Near-Infrared Spectrum Analysis, Raman
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Surface-Enhanced Raman Scattering (SERS) combined with machine learning enables accurate diagnosis of cervical cancer: From molecule to cell to tissue level.

Critical reviews in oncology/hematology Apr 17, 2025
The rising number of cervical cancer cases is placing a heavy economic strain on the country and its people. Improving survival rates hinges on early detection, precise diagnosis, and thorough treatment. Common screening and diagnostic methods like P...
Humans Machine Learning Uterine Cervical Neoplasms Spectrum Analysis, Raman Early Detection of Cancer Female Biomarkers, Tumor
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Single-Molecule SERS Discrimination of Proline from Hydroxyproline Assisted by a Deep Learning Model.

Nano letters Apr 17, 2025
Discriminating low-abundance hydroxylation is a crucial and unmet need for early disease diagnostics and therapeutic development due to the small hydroxyl group with 17.01 Da. While single-molecule surface-enhanced Raman spectroscopy (SERS) sensors c...
Hydroxyproline Hydroxylation Neural Networks, Computer Spectrum Analysis, Raman Deep Learning Proline
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AI-assisted SERS imaging method for label-free and rapid discrimination of clinical lymphoma.

Journal of nanobiotechnology Apr 16, 2025
BACKGROUND: Lymphoma is a malignant tumor of the immune system and its incidence is increasing year after year, causing a major threat to people's health. Conventional diagnosis of lymphoma basically depends on histological images consuming long-time...
Lymphoma Lymphoma, Non-Hodgkin Deep Learning Neural Networks, Computer Humans Spectrum Analysis, Raman Artificial Intelligence Molecular Imaging
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Rapid diagnosis of membranous nephropathy based on kidney tissue Raman spectroscopy and deep learning.

Scientific reports Apr 15, 2025
Membranous nephropathy (MN) is one of the most common glomerular diseases. Although the diagnostic method based on serum PLA2R antibodies has gradually been applied in clinical practice, only 52-86% of PLA2R-associated MN patients show positive anti-...
Glomerulonephritis, Membranous Receptors, Phospholipase A2 Spectrum Analysis, Raman Biopsy Mice Kidney Sensitivity and Specificity Humans Animals Deep Learning
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DeepATsers: a deep learning framework for one-pot SERS biosensor to detect SARS-CoV-2 virus.

Scientific reports Apr 10, 2025
The integration of Artificial Intelligence (AI) techniques with medical kits has revolutionized disease diagnosis, enabling rapid and accurate identification of various conditions. We developed a novel deep learning model, namely DeepATsers based on ...
Neural Networks, Computer COVID-19 Humans Spectrum Analysis, Raman Biosensing Techniques SARS-CoV-2 Spike Glycoprotein, Coronavirus Deep Learning
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Interpretable Multiscale Convolutional Neural Network for Classification and Feature Visualization of Weak Raman Spectra of Biomolecules at Cell Membranes.

ACS sensors Apr 4, 2025
Raman spectroscopy in biological applications faces challenges due to complex spectra, characterized by peaks of varying widths and significant biological background noise. Convolutional neural networks (CNNs) are widely used for spectrum classificat...
Cell Membrane Cholera Toxin Humans Convolutional Neural Networks Neural Networks, Computer Spectrum Analysis, Raman
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