Least-Squares Analysis

Comparative study of machine-and deep-learning based classification algorithms for biomedical Raman spectroscopy (RS): case study of RS based pathogenic microbe identification.

Analytical sciences : the international journal of the Japan Society for Analytical Chemistry 39207655

One key aspect pushing the frontiers of biomedical RS is dedicated machine- or deep- learning (ML or DL) algorithms. Yet, systematic comparative study between ML and DL algorithms has not been conducted for biomedical RS, largely due to the limited a...

Algorithms Bacteria Deep Learning Least-Squares Analysis Machine Learning Spectrum Analysis, Raman

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Production monitoring and quality characterization of black garlic using Vis-NIR hyperspectral imaging integrated with chemometrics strategies.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy 39368183

As a new deep-processing garlic product with notable health benefits, the accurate discrimination of processing stages and prediction of key physicochemical constituents in black garlic are vital for maintaining product quality. This study proposed a...

Chemometrics Discriminant Analysis Garlic Hyperspectral Imaging Least-Squares Analysis Spectroscopy, Near-Infrared Support Vector Machine

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Deep learning and feature reconstruction assisted vis-NIR calibration method for on-line monitoring of key growth indicators during kombucha production.

Food chemistry 39332357

Artificial intelligence (AI) technology is advancing the digitization and intelligence development of the food industry. A promising application is using deep learning-assisted visible near-infrared (vis-NIR) spectroscopy to monitor residual sugar an...

Calibration Deep Learning Least-Squares Analysis Neural Networks, Computer Quality Control Spectroscopy, Near-Infrared

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Orthodontic treatment outcome predictive performance differences between artificial intelligence and conventional methods.

The Angle orthodontist 39230022

OBJECTIVES: To evaluate an artificial intelligence (AI) model in predicting soft tissue and alveolar bone changes following orthodontic treatment and compare the predictive performance of the AI model with conventional prediction models.

Adolescent Adult Alveolar Process Anatomic Landmarks Artificial Intelligence Cephalometry Female Humans Least-Squares Analysis Linear Models Male Neural Networks, Computer Orthodontics, Corrective Treatment Outcome Young Adult

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Does artificial intelligence predict orthognathic surgical outcomes better than conventional linear regression methods?

The Angle orthodontist 39230019

OBJECTIVES: To evaluate the performance of an artificial intelligence (AI) model in predicting orthognathic surgical outcomes compared to conventional prediction methods.

Adolescent Adult Algorithms Anatomic Landmarks Artificial Intelligence Cephalometry Female Forecasting Humans Least-Squares Analysis Linear Models Male Neural Networks, Computer Orthognathic Surgical Procedures Retrospective Studies Treatment Outcome Young Adult

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A nondestructive technique for the sex identification of third instar Cochliomyia macellaria larvae.

Journal of forensic sciences 39223721

Forensic entomology plays an important role in medicolegal investigations by using insects, primarily flies, to estimate the time of colonization. This estimation relies on the development of the flies found at the (death) scene and can be affected (...

Animals Calliphoridae Discriminant Analysis Female Forensic Entomology Humans Larva Least-Squares Analysis Machine Learning Male Spectrophotometry, Infrared

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Simultaneously predicting SPAD and water content in rice leaves using hyperspectral imaging with deep multi-task regression and transfer component analysis.

Journal of the science of food and agriculture 39221962

BACKGROUND: Water content and chlorophyll content are important indicators for monitoring rice growth status. Simultaneous detection of water content and chlorophyll content is of significance. Different varieties of rice show differences in phenotyp...

Chlorophyll Hyperspectral Imaging Least-Squares Analysis Neural Networks, Computer Oryza Plant Leaves Soil Water

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Dielectric spectroscopy technology combined with machine learning methods for nondestructive detection of protein content in fresh milk.

Journal of food science 39394047

To quickly achieve nondestructive detection of protein content in fresh milk, this study utilized a network analyzer and an open coaxial probe to analyze the dielectric spectra of milk samples at 100 frequency points within the 2-20 GHz range, focusi...

Algorithms Animals Cattle Decision Trees Dielectric Spectroscopy Least-Squares Analysis Machine Learning Milk Milk Proteins Support Vector Machine

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Decoding wheat contamination through self-assembled whole-cell biosensor combined with linear and non-linear machine learning algorithms.

Biosensors & bioelectronics 39447529

The contamination of mycotoxins is a serious problem around the world. It has detrimental effects on human beings and leads to tremendous economic loss. It is essential to develop a rapid and non-destructive method for contamination recognition parti...

Algorithms Biosensing Techniques Food Contamination Fungi Humans Least-Squares Analysis Machine Learning Mycotoxins Neural Networks, Computer Support Vector Machine Triticum

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Near-infrared spectroscopy combined with support vector machine for the identification of Tartary buckwheat (Fagopyrum tataricum (L.) Gaertn) adulteration using wavelength selection algorithms.

Food chemistry 39388874

The frequent occurrence of adulterating Tartary buckwheat powder with crop flours in the market necessitates an urgent need for a simple analysis method to ensure the quality of Tartary buckwheat. This study employed near-infrared spectroscopy (NIRS)...

Algorithms Discriminant Analysis Fagopyrum Flour Food Contamination Least-Squares Analysis Spectroscopy, Near-Infrared Support Vector Machine

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

Comparative study of machine-and deep-learning based classification algorithms for biomedical Raman spectroscopy (RS): case study of RS based pathogenic microbe identification.

Production monitoring and quality characterization of black garlic using Vis-NIR hyperspectral imaging integrated with chemometrics strategies.

Deep learning and feature reconstruction assisted vis-NIR calibration method for on-line monitoring of key growth indicators during kombucha production.

Orthodontic treatment outcome predictive performance differences between artificial intelligence and conventional methods.

Does artificial intelligence predict orthognathic surgical outcomes better than conventional linear regression methods?

A nondestructive technique for the sex identification of third instar Cochliomyia macellaria larvae.

Simultaneously predicting SPAD and water content in rice leaves using hyperspectral imaging with deep multi-task regression and transfer component analysis.

Dielectric spectroscopy technology combined with machine learning methods for nondestructive detection of protein content in fresh milk.

Decoding wheat contamination through self-assembled whole-cell biosensor combined with linear and non-linear machine learning algorithms.

Near-infrared spectroscopy combined with support vector machine for the identification of Tartary buckwheat (Fagopyrum tataricum (L.) Gaertn) adulteration using wavelength selection algorithms.

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