Sökning: "Riskstratifiering"

Hittade 3 uppsatser innehållade ordet Riskstratifiering.

  1. 1. Risk Stratification of Endometriosis through Machine Learning using Lifestyle Data : An Extensive Analysis on Lifestyle Data to Reveal Patterns in People with Endometriosis

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

    Författare :Patrick Carrera Jeri; [2023]
    Nyckelord :Lifestyle fators; Machine learning; Risk stratification; Endometriosis; Livsstilsfaktorer; Maskininlärning; Riskstratifiering; Endometrios;

    Sammanfattning : Endometriosis affect 11% of women of reproductive years worldwide. The project made use of lifestyle factors coming from the Lucy application. LÄS MER

  3. 2. Age Prediction in Breast Cancer Risk Stratification : Additive Value of Age Prediction on Healthy Mammography Images in Breast Cancer Risk Models

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

    Författare :Johanna Peterson; [2022]
    Nyckelord :Image Analysis; Age Prediction; Mammography; Breast Cancer; Convolutional Neural Networks.; Bildbehandling; åldersbedömning; mammografi; bröstcancer; Convolutional Neural Networks.;

    Sammanfattning : Breast cancer is the most common cancer type for women worldwide. Early detection is key to improve prognosis and treatment success. A cost-efficient way of finding breast cancer early is mammography screening on a population basis. A major issue with mammography screening is in-between screening cancers. LÄS MER

  4. 3. Privacy Preserving Survival Prediction With Graph Neural Networks

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

    Författare :Stefano Fedeli; [2021]
    Nyckelord :Graph Neural Network; Survival Analysis; Differential Privacy; Clinical Data; Registries; Population Study;

    Sammanfattning : In the development process of novel cancer drugs, one important aspect is to identify patient populations with a high risk of early death so that resources can be focused on patients with the highest medical unmet need. Many cancer types are heterogeneous and there is a need to identify patients with aggressive diseases, meaning a high risk of early death, compared to patients with indolent diseases, meaning a low risk of early death. LÄS MER