AI Medical Compendium Topic

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Spectrum Analysis, Raman

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Au-Ag OHCs-based SERS sensor coupled with deep learning CNN algorithm to quantify thiram and pymetrozine in tea.

Food chemistry
Pesticide residue detection in food has become increasingly important. Herein, surface-enhanced Raman scattering (SERS) coupled with an intelligent algorithm was developed for the rapid and sensitive detection of pesticide residues in tea. By employi...

Plasma Exosome Analysis for Protein Mutation Identification Using a Combination of Raman Spectroscopy and Deep Learning.

ACS sensors
Protein mutation detection using liquid biopsy can be simply performed periodically, making it easy to detect the occurrence of newly emerging mutations rapidly. However, it has low diagnostic accuracy since there are more normal proteins than mutate...

Deep Learning-Assisted Surface-Enhanced Raman Scattering for Rapid Bacterial Identification.

ACS applied materials & interfaces
Bloodstream infection (BSI) is characterized by the presence of viable microorganisms in the bloodstream and may induce systemic immune responses. Early and appropriate antibiotic usage is crucial to effectively treating BSI. However, conventional cu...

Rapid and precise detection of cancers via label-free SERS and deep learning.

Analytical and bioanalytical chemistry
Early, express, and reliable detection of cancer can provide a favorable prognosis and decrease mortality. Tumor biomarkers have been proven to be closely related to tumor occurrence and development. Conventional tumor biomarker detection based on ge...

Recent Research Progress of Surface-Enhanced Raman Scattering Dominated Analysis Strategies in Early Diagnosis of Diseases.

Chemistry, an Asian journal
Timely and powerful diagnostic means can achieve better therapeutic effects, reduce disease torment, and improve survival rate. As a powerful non-invasive spectroscopy technology, surface-enhanced Raman scattering (SERS) have testified to be a great ...

Intelligent convolution neural network-assisted SERS to realize highly accurate identification of six pathogenic .

Chemical communications (Cambridge, England)
Based on label-free SERS technology, the relationship between the Raman signals of pathogenic microorganisms and purine metabolites was analyzed in detail. A deep learning CNN model was successfully developed, achieving a high accuracy rate of 99.7%...

Detecting Pre-Analytically Delayed Blood Samples for Laboratory Diagnostics Using Raman Spectroscopy.

International journal of molecular sciences
In this proof-of-principle study, we systematically studied the potential of Raman spectroscopy for detecting pre-analytical delays in blood serum samples. Spectra from 330 samples from a liver cirrhosis cohort were acquired over the course of eight ...

Surface-enhanced Raman spectroscopy charged probes under inverted superhydrophobic platform for detection of agricultural chemicals residues in rice combined with lightweight deep learning network.

Analytica chimica acta
In this study, surface-enhanced Raman spectroscopy (SERS) charged probes and an inverted superhydrophobic platform were used to develop a detection method for agricultural chemicals residues (ACRs) in rice combined with lightweight deep learning netw...

Early screening of cervical cancer based on tissue Raman spectroscopy combined with deep learning algorithms.

Photodiagnosis and photodynamic therapy
Cervical cancer is the most common reproductive malignancy in the female reproductive system. The incidence rate and mortality rate of cervical cancer among women in China are high. In this study, Raman spectroscopy was used to collect tissue sample ...

Raman spectroscopy combined with a support vector machine algorithm as a diagnostic technique for primary Sjögren's syndrome.

Scientific reports
The aim of this study was to explore the feasibility of Raman spectroscopy combined with computer algorithms in the diagnosis of primary Sjögren syndrome (pSS). In this study, Raman spectra of 60 serum samples were acquired from 30 patients with pSS ...