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Multivariate Analysis

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The same analysis approach: Practical protection against the pitfalls of novel neuroimaging analysis methods.

NeuroImage
Standard neuroimaging data analysis based on traditional principles of experimental design, modelling, and statistical inference is increasingly complemented by novel analysis methods, driven e.g. by machine learning methods. While these novel approa...

Neuroanatomical heterogeneity of schizophrenia revealed by semi-supervised machine learning methods.

Schizophrenia research
UNLABELLED: Schizophrenia is associated with heterogeneous clinical symptoms and neuroanatomical alterations. In this work, we aim to disentangle the patterns of neuroanatomical alterations underlying a heterogeneous population of patients using a se...

Dietary antioxidants and 10-year lung function decline in adults from the ECRHS survey.

The European respiratory journal
The relationship between lung function decline and dietary antioxidants over 10 years in adults from three European countries was investigated.In 2002, adults from three participating countries of the European Community Respiratory Health Survey (ECR...

Accurate and fast feature selection workflow for high-dimensional omics data.

PloS one
We are moving into the age of 'Big Data' in biomedical research and bioinformatics. This trend could be encapsulated in this simple formula: D = S * F, where the volume of data generated (D) increases in both dimensions: the number of samples (S) and...

The neuromorphological caudate-putaminal clustering of neostriate interneurons: Kohonen self-organizing maps and supervised artificial neural networks with multivariate analysis.

Journal of theoretical biology
AIMS: The objective of this study is to investigate the possibility of the neuromorphotopological clustering of neostriate interneurons (NSIN) and their consequent classification into caudate (CIN) and putaminal neuron type (PIN), according to the nu...

Environmental metabolomics with data science for investigating ecosystem homeostasis.

Progress in nuclear magnetic resonance spectroscopy
A natural ecosystem can be viewed as the interconnections between complex metabolic reactions and environments. Humans, a part of these ecosystems, and their activities strongly affect the environments. To account for human effects within ecosystems,...

A happiness degree predictor using the conceptual data structure for deep learning architectures.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Happiness is a universal fundamental human goal. Since the emergence of Positive Psychology, a major focus in psychological research has been to study the role of certain factors in the prediction of happiness. The conventio...

Machine Learning Improves Risk Stratification After Acute Coronary Syndrome.

Scientific reports
The accurate assessment of a patient's risk of adverse events remains a mainstay of clinical care. Commonly used risk metrics have been based on logistic regression models that incorporate aspects of the medical history, presenting signs and symptoms...