Essays about: "Cancer research"
Showing result 1 - 5 of 298 essays containing the words Cancer research.
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1. Increasing Proactive Healthcare: An Automated Approach Within Screening Process For Breast Cancer
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : Breast cancer is the most common cancer and 8 700 individuals in Sweden were diagnosed with breast cancer in 2021. Thanks to improved diagnostic methods and more effective treatment, nine out of ten women who develop breast cancer survive. READ MORE
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2. Robustness Analysis of Perfusion Parameter Calculations
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Cancer is one of the most common causes of death worldwide. When given optimal treatment, however, the risk of severe illness may greatly be reduced. Determining optimal treatment in turn requires evaluation of disease progression and response to potential, previous treatment. READ MORE
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3. Self-Supervised Learning for Tabular Data: Analysing VIME and introducing Mix Encoder
University essay from Lunds universitet/Fysiska institutionenAbstract : We introduce Mix Encoder, a novel self-supervised learning framework for deep tabular data models based on Mixup [1]. Mix Encoder uses linear interpolations of samples with associated pretext tasks to form useful pre-trained representations. READ MORE
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4. Virtual H&E Staining Using PLS Microscopy and Neural Networks
University essay from Lunds universitet/Matematik LTHAbstract : Histopathological examination, crucial in diagnosing diseases such as cancer, traditionally relies on time- and resource-consuming, poorly standardized chemical staining for tissue visualization. This thesis presents a novel digital alternative using generative neural networks and a point light source (PLS) microscope to transform unstained skin tissue images into their stained counterparts. READ MORE
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5. Exploring adaptation of self-supervised representation learning to histopathology images for liver cancer detection
University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknikAbstract : This thesis explores adapting self-supervised representation learning to visual domains beyond natural scenes, focusing on medical imaging. The research addresses the central question: "How can self-supervised representation learning be specifically adapted for detecting liver cancer in histopathology images?" The study utilizes the PAIP 2019 dataset for liver cancer segmentation and employs a self-supervised approach based on the VICReg method. READ MORE