AIMC Topic: Spectrum Analysis, Raman

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Data fusion of near-infrared and Raman spectroscopy: An innovative tool for non-destructive prediction of the TVB-N content of salmon samples.

Food research international (Ottawa, Ont.)
Total volatile basic nitrogen (TVB-N) serves as a crucial indicator for evaluating the freshness of salmon. This study aimed to achieve accurate and non-destructive prediction of TVB-N content in salmon fillets stored in multiple temperature settings...

Meta-Analysis of the Efficacy of Raman Spectroscopy and Machine-Learning-Based Identification of Glioma Tissue.

World neurosurgery
Intraoperative Raman spectroscopy (RS) has been identified as a potential tool for surgeons to rapidly and noninvasively differentiate between diseased and normal tissue. Since the previous meta-analysis on the subject was published in 2016, improvem...

Diagnosis of neuropsychiatric systemic lupus erythematosus by label-free serum microsphere-coupled SERS fingerprints with machine learning.

Biosensors & bioelectronics
Surface-enhanced Raman spectroscopy (SERS) is a powerful optical technique for non-invasive and label-free bioanalysis of liquid biopsy, facilitating to diagnosis of potential diseases. Neuropsychiatric systemic lupus erythematosus (NPSLE) is one of ...

Raman hyperspectroscopy of saliva and machine learning for Sjögren's disease diagnostics.

Scientific reports
Sjögren's disease is an autoimmune disorder affecting exocrine glands, causing dry eyes and mouth and other morbidities. Polypharmacy or a history of radiation to the head and neck can also lead to dry mouth. Sjogren's disease is often underdiagnosed...

Research on disease diagnosis based on teacher-student network and Raman spectroscopy.

Lasers in medical science
Diabetic nephropathy is a serious complication of diabetes, and primary Sjögren's syndrome is a disease that poses a major threat to women's health. Therefore, studying these two diseases is of practical significance. In the field of spectral analysi...

Metabolic profiling of murine radiation-induced lung injury with Raman spectroscopy and comparative machine learning.

The Analyst
Radiation-induced lung injury (RILI) is a dose-limiting toxicity for cancer patients receiving thoracic radiotherapy. As such, it is important to characterize metabolic associations with the early and late stages of RILI, namely pneumonitis and pulmo...

Raman spectroscopy for esophageal tumor diagnosis and delineation using machine learning and the portable Raman spectrometer.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Esophageal cancer is one of the leading causes of cancer-related deaths worldwide. The identification of residual tumor tissues in the surgical margin of esophageal cancer is essential for the treatment and prognosis of cancer patients. But the curre...

Transfer learning improves predictions in lignin content of Chinese fir based on Raman spectra.

International journal of biological macromolecules
Lignin in biomass plays significant role in substitution of synthetic polymer and reduction of energy expenditure, and the lignin content was usually determined by wet chemical methods. However, the methods' heavy workload, low efficiency, huge consu...

Source Tracing of Kidney Injury via the Multispectral Fingerprint Identified by Machine Learning-Driven Surface-Enhanced Raman Spectroscopic Analysis.

ACS sensors
Early diagnosis of drug-induced kidney injury (DIKI) is essential for clinical treatment and intervention. However, developing a reliable method to trace kidney injury origins through retrospective studies remains a challenge. In this study, we desig...

Deep learning-assisted monitoring of trastuzumab efficacy in HER2-Overexpressing breast cancer via SERS immunoassays of tumor-derived urinary exosomal biomarkers.

Biosensors & bioelectronics
Monitoring drug efficacy is significant in the current concept of companion diagnostics in metastatic breast cancer. Trastuzumab, a drug targeting human epidermal growth factor receptor 2 (HER2), is an effective treatment for metastatic breast cancer...