Analysis (PCA) and Linear Discriminant Analysis (LDA) were utilized to classify cell lines using multiple compounds15. Even though analyzing cell lines is an efficient strategy, these results may not be translatable to human or even whole animal studies. Analyzing urine would provide biomarkers that...
Data were explored with principal component analysis (PCA) and classified with linear discriminant analysis (LDA), soft independent modelling by class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA). For discrimination and classification, models were developed within each of ...
Data were explored with principal component analysis (PCA) and classified with linear discriminant analysis (LDA), soft independent modelling by class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA). For discrimination and classification, models were developed within each of ...
The resulting data were analysed using linear discriminant analysis (LDA) and principal component analysis (PCA) to evaluate the E-nose's ability to discriminate between groups. W5S, W1S, W2S, and W2W sensors exhibited the greatest variation in response intensity; in particular, they highlighted...
The resulting data were analysed using linear discriminant analysis (LDA) and principal component analysis (PCA) to evaluate the E-nose's ability to discriminate between groups. W5S, W1S, W2S, and W2W sensors exhibited the greatest variation in response intensity; in particular, they highlighted...
The resulting data were analysed using linear discriminant analysis (LDA) and principal component analysis (PCA) to evaluate the E-nose's ability to discriminate between groups. W5S, W1S, W2S, and W2W sensors exhibited the greatest variation in response intensity; in particular, they highlighted...
The resulting data were analysed using linear discriminant analysis (LDA) and principal component analysis (PCA) to evaluate the E-nose's ability to discriminate between groups. W5S, W1S, W2S, and W2W sensors exhibited the greatest variation in response intensity; in particular, they highlighted...
The resulting data were analysed using linear discriminant analysis (LDA) and principal component analysis (PCA) to evaluate the E-nose's ability to discriminate between groups. W5S, W1S, W2S, and W2W sensors exhibited the greatest variation in response intensity; in particular, they highlighted...
The resulting data were analysed using linear discriminant analysis (LDA) and principal component analysis (PCA) to evaluate the E-nose's ability to discriminate between groups. W5S, W1S, W2S, and W2W sensors exhibited the greatest variation in response intensity; in particular, they highlighted...
(LDA) and principal component analysis (PCA) to evaluate the E-nose’s ability to discriminate between groups. W5S, W1S, W2S, and W2W sensors exhibited the greatest variation in response intensity; in particular, they highlighted differences between obese and non-obese subjects. The LDA plot ...