# name
Application of multiblock techniques in metabolomic and clinical data for the prediction of ventilatory therapies in Covid-19 patients

# metadata.dc.description[].value
Treballs Finals de Grau d'Enginyeria Biomèdica. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona. Curs: 2023-2024. Tutor/Director: Luis Fernández Romero ;  Luis Fernández Romero,
Santiago Marco Colás

# metadata.dc.description.abstract[].value
Multiblock techniques, as the name suggests, are analytical methods that handle datasets 
organized into multiple blocks, each of them representing a set of variables with similar nature. 
These methods aim to model relationships across these blocks, delving into the internal structure 
of the data to uncover patterns that might not be apparent when analysing them individually. In this 
thesis, regularised CCA, PLS and multiblock-PLS-DA (DIABLO) have been applied to Covid-19 
patients’ data to study the behaviour and relationships between two sets of variables, one 
containing metabolomic measures and the other evaluating different clinical features. Additionally, 
two different approaches have been proposed and discussed to incorporate multiblock analysis 
into the prediction of the failure of non-invasive respiratory support in Covid-19 patients. This has 
allowed not only the exploration of the relationship net between blocks but also the identification of
similarities and correlations among the relevant variables in a predictive context. At the end, 
multiblock techniques have shown their potential to extract valuable information from the dataset 
and to optimize and maximize the classification procedure, leading to the identification of three 
variables (anthranilic acid, octanoic acid and malate/succinate ratio) that allow to successfully 
predict the failure of non-invasive respiratory support in Covid-19 patients.

# metadata.dc.rights[].value
cc-by-nc-nd (c) Miquel Porta Valero, 2024

# metadata.dc.source[].value
Treballs Finals de Grau (TFG) - Enginyeria Biomèdica

# metadata.dc.title[].value
Application of multiblock techniques in metabolomic and clinical data for the prediction of ventilatory therapies in Covid-19 patients