Search for dissertations about: "Least absolute shrinkage and selection operator"
Showing result 1 - 5 of 8 swedish dissertations containing the words Least absolute shrinkage and selection operator.
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1. In search of early biomarkers in pancreatic ductal adenocarcinoma using multi-omics and bioinformatics
Abstract : Background: Pancreatic ductal adenocarcinoma (PDAC) is a very aggressive malignancy with a 5-year survival of 10 %. Surgery is the only curative treatment. Unfortunately, few patients are eligible for surgery due to late detection. Thus, we need ways to detect the disease at an earlier stage and for that good screening biomarkers could be used. READ MORE
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2. Covariate Model Building in Nonlinear Mixed Effects Models
Abstract : Population pharmacokinetic-pharmacodynamic (PK-PD) models can be fitted using nonlinear mixed effects modelling (NONMEM). This is an efficient way of learning about drugs and diseases from data collected in clinical trials. READ MORE
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3. Spatial Characterization and Estimation of Intracardiac Propagation Patterns During Atrial Fibrillation
Abstract : This doctoral thesis is in the field of biomedical signal processing with focus on methods for the analysis of atrial fibrillation (AF). Paper I of the present thesis addresses the challenge of extracting spatial properties of AF from body surface signals. READ MORE
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4. Parameter Estimation and Filtering Using Sparse Modeling
Abstract : Sparsity-based estimation techniques deal with the problem of retrieving a data vector from an undercomplete set of linear observations, when the data vector is known to have few nonzero elements with unknown positions. It is also known as the atomic decomposition problem, and has been carefully studied in the field of compressed sensing. READ MORE
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5. Parameter Estimation Using Sparse Modeling: Algorithms and Performance Analysis
Abstract : The idea of representing a signal in a classical computing machine has played a central role in the field of signal processing. The last two decades have witnessed an important breakthrough in this by taking all possible linear transforms and domains into account. READ MORE