AIMC Topic: Spectrophotometry, Infrared
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Machine learning utilising spectral derivative data improves cellular health classification through hyperspectral infra-red spectroscopy.
PloS one
Sep 15, 2020
The objective differentiation of facets of cellular metabolism is important for several clinical applications, including accurate definition of tumour boundaries and targeted wound debridement. To this end, spectral biomarkers to differentiate live a...
A novel method based on infrared spectroscopic inception-resnet networks for the detection of the major fish allergen parvalbumin.
Food chemistry
Sep 6, 2020
We have developed a novel approach that involves inception-resnet network (IRN) modeling based on infrared spectroscopy (IR) for rapid and specific detection of the fish allergen parvalbumin. SDS-PAGE and ELISA were used to validate the new method. T...
Support Vector Machine
Food Analysis
Mice, Inbred BALB C
Food Hypersensitivity
Animals
Mice
Enzyme-Linked Immunosorbent Assay
Electrophoresis, Polyacrylamide Gel
Spectrophotometry, Infrared
Fish Products
Parvalbumins
Fishes
Allergens
Fish Proteins
Neural Networks, Computer
Reproducibility of Results
Predicting bovine tuberculosis status of dairy cows from mid-infrared spectral data of milk using deep learning.
Journal of dairy science
Aug 20, 2020
Bovine tuberculosis (bTB) is a zoonotic disease in cattle that is transmissible to humans, distributed worldwide, and considered endemic throughout much of England and Wales. Mid-infrared (MIR) analysis of milk is used routinely to predict fat and pr...
Monitoring of soluble pectin content in orange juice by means of MIR and TD-NMR spectroscopy combined with machine learning.
Food chemistry
Jun 23, 2020
This study represents a rapid and non-destructive approach based on mid-infrared (MIR) spectroscopy, time domain nuclear magnetic resonance (TD-NMR), and machine learning classification models (ML) for monitoring soluble pectin content (SPC) changes ...
Distinguishing Obstructive Versus Central Apneas in Infrared Video of Sleep Using Deep Learning: Validation Study.
Journal of medical Internet research
May 22, 2020
BACKGROUND: Sleep apnea is a respiratory disorder characterized by an intermittent reduction (hypopnea) or cessation (apnea) of breathing during sleep. Depending on the presence of a breathing effort, sleep apnea is divided into obstructive sleep apn...
Detection of malaria parasites in dried human blood spots using mid-infrared spectroscopy and logistic regression analysis.
Malaria journal
Oct 7, 2019
BACKGROUND: Epidemiological surveys of malaria currently rely on microscopy, polymerase chain reaction assays (PCR) or rapid diagnostic test kits for Plasmodium infections (RDTs). This study investigated whether mid-infrared (MIR) spectroscopy couple...
Metasurface-Based Molecular Biosensing Aided by Artificial Intelligence.
Angewandte Chemie (International ed. in English)
Aug 8, 2019
Molecular spectroscopy provides unique information on the internal structure of biological materials by detecting the characteristic vibrational signatures of their constituent chemical bonds at infrared frequencies. Nanophotonic antennas and metasur...
Using mid-infrared spectroscopy and supervised machine-learning to identify vertebrate blood meals in the malaria vector, Anopheles arabiensis.
Malaria journal
May 30, 2019
BACKGROUND: The propensity of different Anopheles mosquitoes to bite humans instead of other vertebrates influences their capacity to transmit pathogens to humans. Unfortunately, determining proportions of mosquitoes that have fed on humans, i.e. Hum...
Predicting Ewing Sarcoma Treatment Outcome Using Infrared Spectroscopy and Machine Learning.
Molecules (Basel, Switzerland)
Mar 19, 2019
BACKGROUND: Improved outcome prediction is vital for the delivery of risk-adjusted, appropriate and effective care to paediatric patients with Ewing sarcoma-the second most common paediatric malignant bone tumour. Fourier transform infrared (FTIR) sp...
SVM Optimization for Brain Tumor Identification Using Infrared Spectroscopic Samples.
Sensors (Basel, Switzerland)
Dec 18, 2018
The work presented in this paper is focused on the use of spectroscopy to identify the type of tissue of human brain samples employing support vector machine classifiers. Two different spectrometers were used to acquire infrared spectroscopic signatu...
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