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Visar resultat 1 - 5 av 1198 avhandlingar som matchar ovanstående sökkriterier.

  1. 1. Pathway analysis: methods and perspectives

    Författare :Gustavo Stolf Jeuken; Lukas Käll; Mika Gustafsson; KTH; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; pathway analysis; mutual information; survival analysis; enrichment analysis; transcriptomics.; Biotechnology; Bioteknologi;

    Sammanfattning : The amount of data being generated by high throughput molecular biology experiments grows every day, both in quantity and quality. With this comes the desire to have more powerful and comprehensive methods for statistical analysis that have been developed with the nature of this data in mind. LÄS MER

  3. 2. Machine Learning Survival Models : Performance and Explainability

    Författare :Abdallah Alabdallah; Mattias Ohlsson; Thorsteinn Rögnvaldsson; Sepideh Pashami; Erik Frisk; Högskolan i Halmstad; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Survival Analysis; Explainable Artificial Intelligence; Survival Patterns; Counterfactual Explanations; Evaluation Metrics; Concordance Index;

    Sammanfattning : Survival analysis is an essential statistics and machine learning field in various critical applications like medical research and predictive maintenance. In these domains understanding models' predictions is paramount. LÄS MER

  4. 3. Neural Network Approaches To Survival Analysis

    Författare :Jonas Kalderstam; Beräkningsbiologi och biologisk fysik - Genomgår omorganisation; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Survival Analysis; Artificial Neural Networks; Machine Learning; Genetic Algorithms; Evolutionary Algorithms; Fysicumarkivet:2015:Kalderstam;

    Sammanfattning : 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). LÄS MER

  5. 4. Integrative genomic and survival analysis of breast tumors

    Författare :Szilard Nemes; Göteborgs universitet; []
    Nyckelord :MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; biostatistics; cancer; survival analysis; gemonics; DNA copy number aberrations; messenger RNA;

    Sammanfattning : With the continued accumulation of genomic data at ever increasing resolution the challenge ahead lies in reading out meaningful clinical/biological information form the data that can contribute to a better understanding of the cancerous process. The need for novel approaches, new statistical methods is therefore strong. LÄS MER

  7. 5. Correlated random effects models for clustered survival data

    Författare :Frank Eriksson; Göteborgs universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; competing risks; case-cohort; semiparametric; Survival analysis; random effects; routine register; frailty model; Survival analysis; frailty model; competing risks; random effects; case-cohort; routine register; semiparametric;

    Sammanfattning : Frailty models are frequently used to analyse clustered survival data in medical contexts. The frailties, or random effects, are used to model the association between individual survival times within clusters. LÄS MER