Search for dissertations about: "Classification"
Showing result 21 - 25 of 1673 swedish dissertations containing the word Classification.
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21. Statistical inference and time-frequency estimation for non-stationary signal classification
Abstract : This thesis focuses on statistical methods for non-stationary signals. The methods considered or developed address problems of stochastic modeling, inference, spectral analysis, time-frequency analysis, and deep learning for classification. READ MORE
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22. Pressure ulcers - role of the nurse to improve patient safety : prevalence, risk factors, classification and documentation in patients undergoing hip surgery
Abstract : Pressure ulcer is a common complication in hip fracture surgery and convalescence. Earlier prevalence studies have demonstrated a lower prevalence in Southern Europe than in Northern Europe. READ MORE
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23. Clavicle Fractures : Epidemiology, classification, treatment and outcome, with emphasis on displaced lateral clavicle fractures
Abstract : The rate of surgical treatment for clavicle fractures has increased dramatically in the past 20 years, but the necessity for this remains obscure, particularly for displaced lateral clavicle fractures. The overall aim of the thesis is to acquire knowledge that may help guide treatment decisions for clavicle fractures, with an emphasis on displaced lateral fractures. READ MORE
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24. On Data Mining and Classification Using a Bayesian Confidence Propagation Neural Network
Abstract : The aim of this thesis is to describe how a statisticallybased neural network technology, here named BCPNN (BayesianConfidence Propagation Neural Network), which may be identifiedby rewriting Bayes' rule, can be used within a fewapplications, data mining and classification with credibilityintervals as well as unsupervised pattern recognition.BCPNN is a neural network model somewhat reminding aboutBayesian decision trees which are often used within artificialintelligence systems. READ MORE
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25. Voice for Decision Support in Healthcare Applied to Chronic Obstructive Pulmonary Disease Classification : A Machine Learning Approach
Abstract : Background: Advancements in machine learning (ML) techniques and voice technology offer the potential to harness voice as a new tool for developing decision-support tools in healthcare for the benefit of both healthcare providers and patients. Motivated by technological breakthroughs and the increasing integration of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare, numerous studies aim to investigate the diagnostic potential of ML algorithms in the context of voice-affecting disorders. READ MORE