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TITLE:
Design and evaluation of linear prediction models for lipidic families based on 1H-NMR LED spectra - TFG:7016
Handle: https://hdl.handle.net/20.500.11797/TFG7016

Student:Torné Charlez, Pol
Language:en
Title in original language:Design and evaluation of linear prediction models for lipidic families based on 1H-NMR LED spectra
Title in different languages:Design and evaluation of linear prediction models for lipidic families based on 1H-NMR LED spectra
Keywords:linear prediction models, lipid families, nuclear magnetic resonance
Subject:Enginyeria Biomèdica
Abstract:This study focuses on the optimization of the NMR lipid profiling process by supressing the hitherto indispensable step of serum lipid extraction by designing predictive models that can quantify lipid families directly from native serum’s 1H-NMR LED spectrum. For a set of twelve lipidic families an exhaustive process for the development of a linear regression prediction model based on 1H-NMR LED spectra has been successfully conducted. Furthermore, an automatization of the entire linear regression predictive modelling process through the software MATLAB (MathWorks Inc.) and the Partial Least Squares (PLS) Toolbox has been performed and projected into a novel interactive software.
Project director:Correig Blanchar, Xavier
Department:Enginyeria Electrònica, Elèctrica i Automàtica
Education area(s):Enginyeria Biomèdica
Entity:Universitat Rovira i Virgili (URV)
Creation date in repository:2024-04-26
Work's public defense date:2023-06-20
Academic year:2022-2023
Confidenciality:No
Subject areas:Biomedical Engineering
Access rights:info:eu-repo/semantics/openAccess
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