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Coupling of Trastuzumab chromatographic profiling with machine learning tools: A complementary approach for biosimilarity and stability assessment.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences
Biosimilar products present a growing opportunity to improve the global healthcare systems. The amount of accepted variability during the comparative assessments of biosimilar products introduces a significant challenge for both the biosimilar develo...

Sensor Fault Diagnosis Method Based on -Grey Wolf Optimization-Support Vector Machine.

Computational intelligence and neuroscience
Aimed to address the low diagnostic accuracy caused by the similar data distribution of sensor partial faults, a sensor fault diagnosis method is proposed on the basis of Grey Wolf Optimization Support Vector Machine (-GWO-SVM) in this paper. Firstl...

A machine learning-based biological aging prediction and its associations with healthy lifestyles: the Dongfeng-Tongji cohort.

Annals of the New York Academy of Sciences
This study aims to establish a biological age (BA) predictor and to investigate the roles of lifestyles on biological aging. The 14,848 participants with the available information of multisystem measurements from the Dongfeng-Tongji cohort were used ...

Risk prediction of diabetic nephropathy using machine learning techniques: A pilot study with secondary data.

Diabetes & metabolic syndrome
AIMS: This research work presented a comparative study of machine learning (ML), including two objectives: (i) determination of the risk factors of diabetic nephropathy (DN) based on principal component analysis (PCA) via different cutoffs; (ii) pred...

Assessment of Volatile Aromatic Compounds in Smoke Tainted Cabernet Sauvignon Wines Using a Low-Cost E-Nose and Machine Learning Modelling.

Molecules (Basel, Switzerland)
Wine aroma is an important quality trait in wine, influenced by its volatile compounds. Many factors can affect the composition and levels (concentration) of volatile aromatic compounds, including the water status of grapevines, canopy management, an...

A 3D-2D Convolutional Neural Network and Transfer Learning for Hyperspectral Image Classification.

Computational intelligence and neuroscience
As one of the fast evolution of remote sensing and spectral imagery techniques, hyperspectral image (HSI) classification has attracted considerable attention in various fields, including land survey, resource monitoring, and among others. Nonetheless...

Diagnosis of Wilson Disease and Its Phenotypes by Using Artificial Intelligence.

Biomolecules
WD is caused by variants disrupting copper efflux resulting in excessive copper accumulation mainly in liver and brain. The diagnosis of WD is challenged by its variable clinical course, onset, morbidity, and variant type. Currently it is diagnosed...

ARMA-Based Segmentation of Human Limb Motion Sequences.

Sensors (Basel, Switzerland)
With the development of human motion capture (MoCap) equipment and motion analysis technologies, MoCap systems have been widely applied in many fields, including biomedicine, computer vision, virtual reality, etc. With the rapid increase in MoCap dat...

A machine learning approach for the factorization of psychometric data with application to the Delis Kaplan Executive Function System.

Scientific reports
While a replicability crisis has shaken psychological sciences, the replicability of multivariate approaches for psychometric data factorization has received little attention. In particular, Exploratory Factor Analysis (EFA) is frequently promoted as...

Radiomics Analysis Based on Automatic Image Segmentation of DCE-MRI for Predicting Triple-Negative and Nontriple-Negative Breast Cancer.

Computational and mathematical methods in medicine
PURPOSE: To investigate whether quantitative radiomics features extracted from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) could be used to differentiate triple-negative breast cancer (TNBC) and nontriple-negative breast cancer (no...