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Distributional uniformity quantification in heterogeneous prepared dishes combined the hyperspectral imaging technology with Moran's I: A case study of pizza.

Food chemistry
Quality detection is critical in the development of prepared dishes, with distributional uniformity playing a significant role. This study used hyperspectral imaging (HSI) and Moran's I to quantify distributional uniformity, employing pizza as case. ...

A deep learning approach for non-invasive Alzheimer's monitoring using microwave radar data.

Neural networks : the official journal of the International Neural Network Society
Over 50 million people globally suffer from Alzheimer's disease (AD), emphasizing the need for efficient, early diagnostic tools. Traditional methods like Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) scans are expensive, bulky, and s...

Molecular profiling of blood plasma-derived extracellular vesicles derived from Duchenne muscular dystrophy patients through integration of FTIR spectroscopy and machine learning reveals disease signatures.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
PURPOSE: To identify and monitor the FTIR spectral signatures of plasma extracellular vesicles (EVs) from Duchenne Muscular Dystrophy (DMD) patients at different stages with Healthy controls using machine learning models.

Machine learning prediction of stalk lignin content using Fourier transform infrared spectroscopy in large scale maize germplasm.

International journal of biological macromolecules
Lignin has been recognized as a major factor contributing to lignocellulosic recalcitrance in biofuel production and attracted attentions as a high-value product in the biorefinery field. As the traditional wet chemical methods for detecting lignin c...

Plant-based egg washes for use in baked goods: Machine learning and visual parameter analysis.

Journal of food science
Pea protein is one potential environmentally sustainable way of recreating the functionality of eggs in coatings for baked goods. These coatings are commonly applied to enhance visual properties of baked goods that consumers desire, especially color ...

Determination of spectroscopy marker of atherosclerotic carotid stenosis using FTIR-ATR combined with machine learning and chemometrics analyses.

Nanomedicine : nanotechnology, biology, and medicine
Atherosclerotic carotid stenosis (ACS) is a recognized risk factor for ischemic stroke. Currently, the gold diagnostic standard is Doppler ultrasound, the results of which do not provide certainty whether a given person should be qualified for surger...

Raman spectroscopy combined with machine learning and chemometrics analyses as a tool for identification atherosclerotic carotid stenosis from serum.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Atherosclerosis carotid stenosis (ACS) is one of the main causes of stroke. Unfortunately, the highest number of people go to the doctor with an advanced disease or as a result of a stroke, because carotid atherosclerosis does not cause obvious sympt...

Differential plasma cytokine variation following X-ray or proton brain irradiation using machine-learning approaches.

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
PURPOSE: X-ray and proton irradiation have been reported to induce distinct modifications in cytokine expression in vitro and in vivo, suggesting a dissimilar inflammatory response between X-rays and protons. We aimed to investigate the differences i...

Renal Cell Carcinoma Discrimination through Attenuated Total Reflection Fourier Transform Infrared Spectroscopy of Dried Human Urine and Machine Learning Techniques.

International journal of molecular sciences
Renal cell carcinoma (RCC) is the sixth most common cancer in men and is often asymptomatic, leading to incidental detection in advanced disease stages that are associated with aggressive histology and poorer outcomes. Various cancer biomarkers are f...

A Machine Learning-Driven Surface-Enhanced Raman Scattering Analysis Platform for the Label-Free Detection and Identification of Gastric Lesions.

International journal of nanomedicine
BACKGROUND: Gastric lesions pose significant clinical challenges due to their varying degrees of malignancy and difficulty in early diagnosis. Early and accurate detection of these lesions is crucial for effective treatment and improved patient outco...