Sökning: "Malignant Melanoma"

Visar resultat 1 - 5 av 29 uppsatser innehållade orden Malignant Melanoma.

  1. 1. CRISPR Screen to Identify Genes Regulating Melanoma Cell Invasiveness

    Master-uppsats, KTH/Proteinvetenskap

    Författare :Emma Kroon; [2023]
    Nyckelord :CRISPR-Cas9; gene knockout; viral packaging; transduction; invasionstest; CRISPR-Cas9; genknockout; viruspackning; transduction; invasion assay;

    Sammanfattning : Maligna cancerceller har förmågan att sprida sig okontrollerat i kroppen och metastasera till avlägsna organ. Kritiskt i metastaserings processen är cancercellers förmåga att invadera närliggande vävnader innan de sprider sig vidare ut i kroppen. LÄS MER

  3. 2. A Comparison of Convolutional Neural Networks used in Melanoma Detection : With transfer learning on the PAD-UFES-20 and ISIC datasets

    Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Abdi Gobena; [2023]
    Nyckelord :Machine learning; Neural networks; Skin cancer; PAD-UFES-20; ISIC; Maskininlärning; Neuronnätverk; Hudcancer; PAD-UFES-20; ISIC;

    Sammanfattning : Skin cancer is one of the most common forms of cancer, of which melanoma is the most lethal. Early detection is critical to long term survival rates. The use of machine learning to detect melanoma shows promising results in detecting malignant forms. LÄS MER

  4. 3. Determining Important Features for Melanoma Classification Through Feature Selection

    Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Vilmer Jonsson; Tor Strimbold; [2023]
    Nyckelord :;

    Sammanfattning : Skin cancer is a common disease and malignant melanoma is the most dangerous form of it. Although dangerous, the survival rate of melanoma patients is high if the diagnosis is made at an early stage. Computer aided diagnostics has been shown to have potential in accurately diagnosing the disease utilizing machine learning. LÄS MER

  5. 4. Design, implementation and evaluation of a deep learning prototype to classify non-pigmented malignant skin cancer from dermatoscopic images

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Maria del Pilar Aguilera Manzanera; [2022]
    Nyckelord :Melanoma; Skin cancer; Dermatoscopy; Image classification; Machine learning; Artificial intelligence; Convolutional neural networks; Dermatology; Squamous cell carcinoma; Basal cell carcinoma; Actinic keratosis; Computer-aided Diagnostics; Digital dermatology; Technology and Engineering;

    Sammanfattning : The current trends for most fair-skinned populations are that the incidence of melanoma and non-pigmented skin lesions is growing, and this growing trend will continue for the upcoming years. The emergence of deep learning networks and their promising results in solving real-world healthcare problems and improving diagnostic accuracy opens new possibilities. LÄS MER

  7. 5. Cancer i Sverige - En deskriptiv analys av regionala skillnader

    Kandidat-uppsats, Lunds universitet/Statistiska institutionen

    Författare :Anna Gustafsson; [2021]
    Nyckelord :Business and Economics;

    Sammanfattning : This paper sets out to investigate regional differences in cancer incidence and mortality in Sweden. By using descriptive analysis, the aim is to detect regional trends and patterns. Results show that cancer incidence is higher in the south of Sweden compared to the north, especially in Skin cancer (C44) and Malignant melanoma (C43). LÄS MER