AIMC Topic: Spectrometry, Fluorescence
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Decoding Hidden Features in Near-Infrared Fluorescence Spectra of Single-Walled Carbon Nanotubes via Machine Learning for Multiplexed Virus Identification.
ACS nano
Jul 8, 2025
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
Jul 8, 2025
: 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
Jul 5, 2025
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
Jul 1, 2025
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...
Machine Learning-Driven Multi-Emission Fluorescence Array for Simultaneous Size Discrimination and Quantification of Gold Nanoparticles.
Analytical chemistry
Jul 1, 2025
Gold nanoparticles (AuNPs) exhibit size-dependent environmental behaviors and bioaccumulation risks, necessitating precise characterization of their hydrodynamic dimensions and concentrations for toxicity assessment. Existing analytical platforms are...
Machine learning-assisted ratiometric fluorescence sensor array for recognition of multiple quinolones antibiotics.
Food chemistry
Jun 30, 2025
Developing analytical methods for simultaneous detection of multiple antibiotic residues is crucial for environmental protection and human health. In this study, a dual lanthanide fluorescence probe (GDP-Eu-Tb) based on nucleotides has been designed....
Machine Learning-Assisted Multicolor Fluorescence Assay for Visual Data Acquisition and Intelligent Inspection of Multiple Food Hazards Regardless of Matrix Interference.
ACS sensors
Jun 27, 2025
Regarding the significant health risks of pesticide residue in foods, while current sensors still suffer from limited efficiency and stability, as well as difficulties in qualitative identification and quantitative detection of mixtures, development ...
The fluorescence spectrum combined with a broad learning system to characterize the content of difenoconazole in cabbage.
Analytical methods : advancing methods and applications
Jun 12, 2025
Pesticide residue detection plays an important role in vegetable quality and food safety. In this work, we propose a method for detecting difenoconazole pesticide residues based on fluorescence spectroscopy technology and machine learning algorithms....
Accurate Identification of MDMB-Type Synthetic Cannabinoids through Design of Dual Excited-State Intramolecular Proton Transfer Site Probe and Deep-Learning.
Analytical chemistry
Jun 10, 2025
Synthetic cannabinoids, a novel class of highly toxic psychoactive substances with various disguised forms, have posed significant risks to public safety, and their weak reactivity presents a substantial challenge for swift and accurate analysis. In ...
Field-Portable Technology for Illicit Drug Discrimination via Deep Learning of Hybridized Reflectance/Fluorescence Spectroscopic Fingerprints.
Analytical chemistry
May 20, 2025
Novel psychoactive substances (NPS) pose one of the greatest challenges across the illicit drug landscape. They can be highly potent, and coupled with rapid changes in structure, tracking and identifying these drugs is difficult and presents users wi...
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