Sökning: "lung cancer"

Visar resultat 6 - 10 av 152 uppsatser innehållade orden lung cancer.

  1. 6. Comparison of deep learning and model-based approaches for spatial profiling of the immune tumor environment on multiplex image data

    Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

    Författare :Esraa Ahmed; [2023]
    Nyckelord :;

    Sammanfattning : The demographics of the tumor microenvironment (TME) impact the Immunotherapy responses for lung cancer patients. Given the heterogeneity of immune cells present within TME, the distribution patterns of different subpopulations of T-cells can be exploited to predict short-term or long-term survival of lung cancer patients. LÄS MER

  3. 7. Clinical Assessment of Deep Learning-Based Uncertainty Maps in Lung Cancer Segmentation

    Master-uppsats, KTH/Skolan för kemi, bioteknologi och hälsa (CBH)

    Författare :Federica Carmen Maruccio; [2023]
    Nyckelord :3D U-Net; Contouring; Clinical validation; Deep learning; Lung cancer; Monte Carlo dropout; Probability map; Reliability diagram; Segmentation; Uncertainty map;

    Sammanfattning : Prior to radiation therapy planning, tumours and organs at risk need to be delineated. In recent years, deep learning models have opened the possibility of automating the contouring process, speeding up the procedures and helping clinicians. LÄS MER

  4. 8. Correlation between Surface and Tumour Motion in Lung Cancer - including Deep Learning Perspectives

    Master-uppsats, Lunds universitet/Sjukhusfysikerutbildningen

    Författare :Caisa Kjellström; [2023]
    Nyckelord :Medicine and Health Sciences;

    Sammanfattning : Purpose: The purpose of this master thesis was to retrospectively investigate correlation between surface and tumour motion in lung cancer patients, alongside deep learning applications of the results. Additional correlations such as age, tumour volume and anatomical placement of the tumour were also investigated. LÄS MER

  5. 9. Gene Biomarker Identification by Distinguishing Between Small-Cell and Non-Small Cell Lung Cancer Through a Module-Based Approach

    Magister-uppsats, Högskolan i Skövde/Institutionen för biovetenskap

    Författare :Noor Haval Jamal; [2023]
    Nyckelord :;

    Sammanfattning : Lung cancer is the leading cause of cancer-related deaths worldwide and is divided into two broad histological types, small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). Network module-based approach is applied to lung cancer subtypes in order to analyze and compare the results with previous literature and thus discover new genetic biomarkers and/or confirm previously discovered ones. LÄS MER

  7. 10. Constructing and analyzing a gene-gene interaction network to identify driver modules in lung cancer using a clustering method

    Magister-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Marcell Szalai; [2023]
    Nyckelord :Lung Cancer; Driver Modules; Artificial Intelligence; Clustering; Gene-Gene Interaction Network; Signaling Pathways;

    Sammanfattning : Cancer is a complex disease with diverse genetic changes that pose significant treatment challenges due to its heterogeneity. Identifying driver modules, which are crucial for cancer progression, has been aided by artificial intelligence (AI) techniques. However, existing approaches lack specificity, particularly for cancer types like lung cancer. LÄS MER