Application of Ensemble Machine Learning to Metabolomic Data ...

Integration of ensemble machine learning feature-ranking tools into our analysis of metabolomic data identified new potential targets in ...

Keywords: Macrophage polarization; Metabolomics; AI/ML methods; ODE models; Topological data analysis. 25. 26. 1. Introduction. 27. The tumor ...

Application of ensemble deep neural network to metabolomics studies

However, data mining methods alternative to PLS are also important and needed in several cases; thus, machine learning approaches such as ...

Metabolomic machine learning predictor for diagnosis and ... - NCBI

Machine learning, a widely used artificial intelligence (AI) approach, automatically analyzes complex data in many fields of biomedical science, ...

Applications of machine learning in metabolomics - Frontiers

In the same way, ML methods are utilized for the classification, regression, or clustering of highly complex metabolomic data. This review discusses how disease ...

Application of ensemble deep neural network to metabolomics studies

Deep neural network (DNN) is a useful machine learning approach, although its applicability to metabolomics studies has rarely been explored.

Metabolomic machine learning predictor for diagnosis and ... - Nature

Although metabolomics enables the measurement of hundreds of metabolites presenting in clinical samples, sophisticated data processing and ...

bioRxiv Bioinfo on X: "Application of Ensemble Machine Learning to ...

Application of Ensemble Machine Learning to Metabolomic Data Identifies Metabolites Associated with Macrophage Polarization ...

Using Machine Learning to Identify Metabolomic Signatures ... - NCBI

Untargeted plasma metabolomic profiling combined with machine learning (ML) may lead to discovery of metabolic profiles that inform our understanding of ...

Machine Learning in Metabolomics: Powerful Insights and ...

DT can handle both categorical and numerical data, and can provide interpretable and visual results. DT has been used for various applications ...

Application of ensemble deep neural network to metabolomics studies

... At present, although traditional machine learning methods such as principal component analysis (PCA) [16], random forest (RF) [17], and ...

Machine learning for metabolomics research in drug discovery

Metabolomics data is obtained using analytical techniques, particularly nuclear magnetic resonance (NMR) spectrometry or mass spectrometry (MS)-based methods, ...

Machine Learning Identifies Metabolic Signatures that Predict the ...

Metabolomic data are highly dimensional and often correlated. Machine learning can reduce the dimensionality of metabolomic data sets and ...

TIGER: technical variation elimination for metabolomics data using ...

Keywords: metabolomics, machine learning, ensemble learning, predictive modelling, longitudinal analysis ... The application scope of this ensemble learning.

Deep metabolome: Applications of deep learning in metabolomics

However, the applications of deep learning in metabolomics are still relatively low compared to others omics. Currently, data pre-processing using convolutional ...

Implementation of ensemble machine learning algorithms on exome ...

In the present study, various ML algorithms were explored on twenty exome datasets, belonging to 5 cancer types. Initially, a data clean-up was ...

Application of ensemble deep neural network to metabolomics studies

Alakwaa, Deep learning accurately predicts estrogen receptor status in breast cancer metabolomics data, J. ... Dietterich, Ensemble methods in machine learning, ...

Automated Machine Learning and Explainable AI (AutoML-XAI) for ...

Metabolomics generates complex data necessitating advanced computational methods for generating biological insight. While machine learning ...

Application of ensemble machine learning algorithms on lifestyle ...

This study looked at novel data sources for cardiovascular risk prediction including detailed lifestyle questionnaire and continuous blood pressure monitoring

Machine Learning Using Neural Networks for Metabolomic Pathway ...

In this chapter, we will be reviewing the use of machine learning for metabolic pathway analyses, with a step-by-step focus on the use of deep learning.