Sökning: "Tumor Classification"

Visar resultat 6 - 10 av 77 avhandlingar innehållade orden Tumor Classification.

  1. 6. Genetic Analyses of Tumor Progression in Colorectal Cancer

    Författare :Kristina Lagerstedt; Göteborgs universitet; []
    Nyckelord :colorectal cancer; tumor progression; microarray; DNA aberration; gene expression; microRNA; structural variation;

    Sammanfattning : Colorectal tumors are responsible for more than 600 000 deaths per year worldwide and thereby constitute the second most common cause of cancer related mortality. Early detection is related to improved prognosis and identification of genetic biomarkers would meliorate available diagnostic tools. LÄS MER

  3. 7. Prognosis based classification and tumor biology of uterine sarcomas

    Författare :Elin Hardell; Karolinska Institutet; Karolinska Institutet; []
    Nyckelord :;

    Sammanfattning : Uterine stromal sarcomas are a heterogenous group of tumors ranging from low-grade stromal sarcomas with a relatively good survival but high risk of recurrence, to undifferentiated uterine sarcomas with a far worse prognosis. Little is known about their biology, and prognostic markers are lacking. LÄS MER

  4. 8. cancer subtype identification using cluster analysis on high-dimensional omics data

    Författare :Linda Vidman; Patrik Rydén; Jun Yu; Erik Kristiansson; Umeå universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; cluster analysis; cancer; classification;

    Sammanfattning : Identification and prediction of cancer subtypes are important parts in the development towards personalized medicine. By tailoring treatments, it is possible to decrease unnecessary suffering and reduce costs. Since the introduction of next generation sequencing techniques, the amount of data available for medical research has increased rapidly. LÄS MER

  5. 9. Resource efficient automatic segmentation of medical images

    Författare :Minh Hoang Vu; Tommy Löfstedt; Tufve Nyholm; Anders Garpebring; Joakim Jonsson; Örjan Smedby; Umeå universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; radiotherapy; medical imaging; deep learning; convolutional neural network; generative adversarial network; data augmentation; semantic segmentation; classification; activation map compression; radiofysik; radiation physics;

    Sammanfattning : Cancer is one of the leading causes of death worldwide. In 2020, there were around 10 million cancer deaths and nearly 20 million new cancer cases in the world. Radiation therapy is essential in cancer treatments because half of the cancer patients receive radiation therapy at some point. LÄS MER

  7. 10. Deep Learning Methods for Classification of Glioma and its Molecular Subtypes

    Författare :Muhaddisa Barat Ali; Chalmers tekniska högskola; []
    Nyckelord :MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; 1p 19q codeletion; generative adversarial network; convolutional neural network; glioma subtype classification; IDH mutation.; Deep learning; cycleGAN; convolutional autoencoder;

    Sammanfattning : Diagnosis and timely treatment play an important role in preventing brain tumor growth. Clinicians are unable to reliably predict LGG molecular subtypes from magnetic resonance imaging (MRI) without taking biopsy. Accurate diagnosis prior to surgery would be important. LÄS MER