AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Spectroscopy, Near-Infrared

Showing 41 to 50 of 260 articles

Clear Filters

Multivariate Modelling and Prediction of High-Frequency Sensor-Based Cerebral Physiologic Signals: Narrative Review of Machine Learning Methodologies.

Sensors (Basel, Switzerland)
Monitoring cerebral oxygenation and metabolism, using a combination of invasive and non-invasive sensors, is vital due to frequent disruptions in hemodynamic regulation across various diseases. These sensors generate continuous high-frequency data st...

Determination and visualization of moisture content in Camellia oleifera seeds rapidly based on hyperspectral imaging combined with deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Moisture content (MC) is crucial for the storage, transportation, and processing of Camellia oleifera seeds. The purpose of this study was to investigate the feasibility for detecting MC in Camellia oleifera seeds using visible near-infrared hyperspe...

Lightweight deep learning algorithm for real-time wheat flour quality detection via NIR spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Wheat flour quality, determined by factors such as protein and moisture content, is crucial in food production. Traditional methods for analyzing these parameters, though precise, are time-consuming and impractical for large-scale operations. This st...

Rapid detection of microplastics in chicken feed based on near infrared spectroscopy and machine learning algorithm.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The main objective of this study was to evaluate the potential of near infrared (NIR) spectroscopy and machine learning in detecting microplastics (MPs) in chicken feed. The application of machine learning techniques in building optimal classificatio...

Enhancing beer authentication, quality, and control assessment using non-invasive spectroscopy through bottle and machine learning modeling.

Journal of food science
Fraud in alcoholic beverages through counterfeiting and adulteration is rising, significantly impacting companies economically. This study aimed to develop a method using near-infrared (NIR) spectroscopy (1596-2396 nm) through the bottle, along with ...

Prediction of Deoxynivalenol contamination in wheat kernels and flour based on visible near-infrared spectroscopy, feature selection and machine learning modelling.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Contamination of wheat by the mycotoxin Deoxynivalenol (DON), produced by Fusarium fungi, poses significant challenges to the quality of crop yield and food safety. Visible and near-infrared (vis-NIR) spectroscopy has emerged as a promising, non-dest...

Regression study on fruit-setting days of purple eggplant fruit based on in situ VIS-NIRS and attention cycle neural network.

Journal of food science
In the intelligent harvesting of eggplant, the lack of in situ identification technology makes it challenging to determine the maturity of purple eggplant fruit. The length of the fruit-setting date can determine when the eggplant is ready to be harv...

Application of functional near-infrared spectroscopy and machine learning to predict treatment response after six months in major depressive disorder.

Translational psychiatry
Depression treatment responses vary widely among individuals. Identifying objective biomarkers with predictive accuracy for therapeutic outcomes can enhance treatment efficiency and avoid ineffective therapies. This study investigates whether functio...

Prediction of health anxiety using resting-state functional near-infrared spectroscopy and machine learning.

Journal of affective disorders
BACKGROUND: The role of cortical networks in health anxiety remain poorly understood. This study aimed to develop a predictive model for health anxiety, using a machine-learning approach based on resting-state functional connectivity (rsFC) with func...

Using near-infrared hyperspectral imaging combined with machine learning to predict the components and the origin of Radix Paeoniae Rubra.

Analytical methods : advancing methods and applications
The efficacy and safety of drugs are closely related to the geographical origin and quality of the raw materials. This study focuses on using near-infrared hyperspectral imaging (NIR-HSI) combined with machine learning algorithms to construct content...