Search for dissertations about: "prediktion"
Showing result 16 - 20 of 41 swedish dissertations containing the word prediktion.
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16. Neural Network Approaches To Survival Analysis
Abstract : Predicting the probable survival for a patient can be very challenging for many diseases. In many forms of cancer, the choice of treatment can be directly impacted by the estimated risk for the patient. This thesis explores different methods to predict the patient's survival chances using artificial neural networks (ANN). READ MORE
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17. On Radio Frequency Behavioral Modeling : Measurement Techniques, Devices and Validation Aspects
Abstract : Effektförstärkare för radiofrekvensapplikationer utgör fortfarande ett av de största problemen i trådlösa kommunikationssystem. Detta beror på att dessa förstärkare är ickelinjära, har låg energieffektivitet och ger mycket distortioner. Bättre verktyg för att förstå och korrigera dessa beteenden är nödvändiga. READ MORE
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18. Genomic Profiling, Mutations and Deranged Signaling in Esophageal Cancer and Hereditary Colorectal Cancer
Abstract : Esophageal cancer and colorectal cancer represents two major types of gastrointestinal tumors. Though refined surgery and introduction of novel chemotherapeutics have improved outcome, more than 2500 Swedes die from these diseases every year. Novel markers for early diagnosis, prognosis and treatment prediction are therefore needed. READ MORE
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19. Prediction Methods for High Dimensional Data with Censored Covariates
Abstract : While access to data steadily increases, not all data are straight-forward to use for prediction. Censored data are common in several industrial scenarios, and typically arise when there are some limitations to measuring equipment such as for instance concentration measuring equipment in chemistry or signal receivers in signal processing. READ MORE
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20. On the Metric-based Approach to Supervised Concept Learning
Abstract : A classifier is a piece of software that is able to categorize objects for which the class is unknown. The task of automatically generating classifiers by generalizing from examples is an important problem in many practical applications. This problem is often referred to as supervised concept learning, and has been shown to be relevant in e.g. READ MORE