AIMC Topic: Spectroscopy, Fourier Transform Infrared

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Usefulness of Data Simulation for Training Deep Learning Denoising Algorithms in Infrared Spectral Histology.

Analytical chemistry
This study investigates the use of simulated data to train deep learning models for denoising infrared spectral images of paraffin-embedded tissue sections in clinical applications. Noise in Fourier-transform infrared spectroscopy poses significant c...

ATR-FTIR Spectroscopy of Saliva and Machine Learning as a Screening Test for Sjögren Disease.

Analytical chemistry
Sjögren's disease is often an underdiagnosed autoimmune condition that primarily affects the exocrine glands, resulting in symptoms such as dry eyes and dry mouth. Diagnostic challenges stem from nonspecific symptoms, the absence of definitive biomar...

Discrimination of urine infrared spectral biomarkers for early-stage chronic kidney disease patients using attenuated total reflectance fourier transform infrared spectrometry.

Clinica chimica acta; international journal of clinical chemistry
Chronic Kidney Disease (CKD) is a highly prevalent non-communicable disorder lacking a gold standard method for diagnosis. Early-stage CKD remains undiagnosed and untreated leading to the disease progression. The study aimed to discriminate urine sam...

Rapid reagent free COVID19 detection using MEMS based FTIR spectroscopy and machine learning in NIR and MIR regions.

Scientific reports
This study presents rapid, reagent-free detection of COVID-19 using miniaturized MEMS-based Fourier-transform infrared (FTIR) spectrometers integrated with machine learning models. Two portable spectrometers analyze 363 nasopharyngeal swab samples st...

Use of IR Biotyper as a feasible methodology to type .

Microbiology spectrum
UNLABELLED: is one of the most frequently reported healthcare-associated pathogens. The current gold standard approach to perform the epidemiological typing of these bacteria is Whole Genome Sequencing (WGS), which is an expensive and challenging pr...

A comparative analysis of deep learning architectures for thyroid tissue classification with hyperspectral imaging.

Scientific reports
Hyperspectral imaging has shown significant applicability in the medical field, particularly for its ability to represent spectral information that can differentiate specific biomolecular characteristics in tissue samples. However, the complexity of ...

FTIR spectroscopy imaging coupled with machine learning reveals biochemical changes in the brains of diabetic mice.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Diabetic encephalopathy is a progressive complication of type 2 diabetes, yet its region-specific biochemical changes remain unclear. In this study, we applied Fourier Transform Infrared Microspectroscopy (FTIRM) to assess metabolic alterations in th...

Species discrimination and VIP-stacking quantitative models for Curcumae Rhizoma utilizing multi-modal spectra combined with machine learning algorithm.

Journal of pharmaceutical and biomedical analysis
Curcumae Rhizoma (Ezhu) is a multi-species herbal medicine with excellent medicinal value and development potential. However, challenges such as the difficulty in differentiating its varieties and the limitations of current methods for determining mi...

Detection of Unlabeled Polystyrene Micro- and Nanoplastics in Mammalian Tissue by Optical Photothermal Infrared Spectroscopy.

Analytical chemistry
In this study, we investigate the efficacy of optical photothermal infrared (O-PTIR) spectroscopy, also known as mid-infrared photothermal (MIP) microscopy, for label-free and nondestructive detection of micro- and nanoplastics (MNPs) down to diamete...