Search for dissertations about: "Rebecka Jörnsten"

Found 5 swedish dissertations containing the words Rebecka Jörnsten.

  2. 1. Data-driven quality management using explainable machine learning and adaptive control limits

    Author : Niklas Fries; Patrik Rydén; Jun Yu; Rebecka Jörnsten; Umeå universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; quality management; machine learning; local explanation methods; process adjustment policies; simulation; matematisk statistik; Mathematical Statistics; data science; data science;

    Abstract : In industrial applications, the objective of statistical quality management is to achieve quality guarantees through the efficient and effective application of statistical methods. Historically, quality management has been characterized by a systematic monitoring of critical quality characteristics, accompanied by manual and experience-based root cause analysis in case of an observed decline in quality. READ MORE

  4. 2. Large scale integration and interactive exploration of cancer data – with applications to glioblastoma

    Author : Patrik Johansson; Sven Nelander; Rebecka Jörnsten; Lene Uhrbom; Gary Bader; Uppsala universitet; []
    Keywords : MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Glioblastoma; data integration; network modeling; interactive exploration; precision medicine; Oncology; Onkologi; Molekylär medicin; Molecular Medicine; Statistics; Statistik;

    Abstract : Glioblastoma is the most common malignant brain tumor, with a median survival of approximately 15 months. The standard of care treatment consists of surgical resection followed by radiotherapy and chemotherapy, where chemotherapy only prolongs survival by approximately 3 months. READ MORE

  5. 3. Hidden patterns that matter : statistical methods for analysis of DNA and RNA data

    Author : Therese Kellgren; Patrik Rydén; Sara Sjöstedt de Luna; Rebecka Jörnsten; Umeå universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Genome; Next-generation sequence; statistics; microarrays; bacteria; antibiotic resistance; inherited diseases; Co-expression networks; centralization within subgroups;

    Abstract : Understanding how the genetic variations can affect characteristics and function of organisms can help researchers and medical doctors to detect genetic alterations that cause disease and reveal genes that causes antibiotic resistance. The opportunities and progress associated with such data come however with challenges related to statistical analysis. READ MORE

  6. 4. Normalization and analysis of high-dimensional genomics data

    Author : Mattias Landfors; Patrik Rydén; Rebecka Jörnsten; Umeå universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; normalization; pre-processing; microarray; downstream analysis; evaluation; sensitivity; bias; genomics data; gene expression; spike-in data; ChIP-chip; Mathematical Statistics; matematisk statistik;

    Abstract : In the middle of the 1990’s the microarray technology was introduced. The technology allowed for genome wide analysis of gene expression in one experiment. Since its introduction similar high through-put methods have been developed in other fields of molecular biology. READ MORE

  7. 5. Modeling glioblastoma growth patterns and their mechanistic origins

    Author : Emil Rosén; Sven Nelander; Rebecka Jörnsten; Philip Gerlee; Kristin Swanson; Uppsala universitet; []
    Keywords : MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; glioblastoma; invasion; image analysis; neural networks; Mathematics with specialization in Applied Mathematics; Matematik med inriktning mot tillämpad matematik; Oncology; Onkologi; Molekylär medicin; Molecular Medicine;

    Abstract : Glioblastoma (GBM) is the most common and aggressive primary brain cancer. GBM cells migrate away from the primary lesion and invade healthy brain tissue. The invading cells escape surgical resection, radiotherapy and develop resistance to chemotherapy. Consequently, despite treatment, recurrence is inevitable, and survival is only 14 months. READ MORE