AIMC Topic: Spectrometry, Fluorescence

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Oil species identification technique developed by Gabor wavelet analysis and support vector machine based on concentration-synchronous-matrix-fluorescence spectroscopy.

Marine pollution bulletin
Concentration-synchronous-matrix-fluorescence (CSMF) spectroscopy was applied to discriminate the oil species by characterizing the concentration dependent fluorescence properties of petroleum related samples. Seven days weathering experiment of 3 cr...

Application of unfolded principal component analysis-radial basis function neural network for determination of celecoxib in human serum by three-dimensional excitation-emission matrix fluorescence spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
This study describes a simple and rapid approach of monitoring celecoxib (CLX). Unfolded principal component analysis-radial basis function neural network (UPCA-RBFNN) and excitation-emission spectra were combined to develop new model in the determin...

Differentiating estuarine dissolved organic matter composition by unsupervised and supervised machine learning.

Water research
Differentiating the composition of Dissolved Organic Matter (DOM) in estuaries is a major environmental concern, as the DOM characteristics are closely linked to biogeochemical and ecological considerations (e.g. water properties and trophic cycling)...

Deep machine learning-assisted MOF@COF fluorescence/colorimetric dual-mode intelligent ratiometric sensing platform for sensitive glutathione detection.

Talanta
Glutathione (GSH) levels have been linked to aging and the pathogenesis of various diseases, highlighting the necessity for the development of sensitive analytical methods for GSH to facilitate disease diagnosis and treatment. In this study, we synth...

One-pot synthesized multifunctional Zn-MOF/HOF heterostructure sensor array assisted by machine learning for efficient capture, target discrimination and optosmart sensing of doxycycline analogs.

Journal of hazardous materials
The ideal multifunctional platform that combines the capabilities of effective capture, sensitive detection, and accurate identification of doxycycline analogs (DCs) remains a serious challenge for ensuring the environment and food security. This wor...

Dual-mode nanosensor for sensitive detection of methotrexate based on fluorescence technology and deep learning algorithms.

Analytica chimica acta
BACKGROUND: Methotrexate (MTX) in the body can result in severe, potentially life-threatening side effects. As a result, it is imperative to establish a dependable, precise, and specific method for detecting MTX. However, conventional sensors often s...

Decoding Hidden Features in Near-Infrared Fluorescence Spectra of Single-Walled Carbon Nanotubes via Machine Learning for Multiplexed Virus Identification.

ACS nano
Single-walled carbon nanotubes (SWCNTs) exhibit rich spectral diversity in their near-infrared (nIR) fluorescence, offering strong potential for multiplexed optical sensing via diverse signal features, even with a single sensor. However, conventional...

Serum-Based Detection of Pancreatic and Ovarian Cancer via a Nanoparticle-Enhanced Fluorescence Array and Machine Learning.

Analytical chemistry
: Early detection of oncological diseases such as pancreatic ductal adenocarcinoma (PDAC) and ovarian cancer (OV) is pivotal for successful treatment but remains a significant challenge due to the lack of sensitive and specific diagnostic tests. Fluo...

Rapid diagnosis of lung cancer by multi-modal spectral data combined with deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Lung cancer is a malignant tumor that poses a serious threat to human health. Existing lung cancer diagnostic techniques face the challenges of high cost and slow diagnosis. Early and rapid diagnosis and treatment are essential to improve the outcome...

Deep Learning-Assisted Nanocavity Sensor for Amphiphilic Biomarker Analysis.

Analytical chemistry
Fluorescence enhancement using nanocavity structures is a promising approach for rapid detection of amphiphilic biomarkers, which are essential for diagnosing diseases such as cancer and infections. This paper presents the use of a silver nanocube (A...