Sökning: "binary tumour classification"
Visar resultat 1 - 5 av 6 uppsatser innehållade orden binary tumour classification.
1. A Machine Learning Approach to Skin Cancer Delineation on Photoacoustic Imaging
Master-uppsats, Lunds universitet/Fysiska institutionen; Lunds universitet/Beräkningsbiologi och biologisk fysik - Genomgår omorganisationSammanfattning : Skin cancer is a growing public health concern due to its prevalence among the population. Current clinical procedures require high invasiveness and multiple surgeries, which are responsible for patient discomfort and high medical expenses. LÄS MER
2. A comparison between fully-supervised and self-supervised deep learning methods for tumour classification in digital pathology data
Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för system- och rymdteknikSammanfattning : Whole Slide Images (WSIs) are digital scans containing rich pathology information. There are many available WSI datasets that can be used for a wide range of purposes such as diagnostic tasks and analysis, but the availability of labeled WSI datasets is very limited since the annotation process is both very costly and time consuming. LÄS MER
3. Natural Language Processing for Patient Data in Clinical Decision Support Systems
Master-uppsats, Lunds universitet/Avdelningen för Biomedicinsk teknikSammanfattning : In Sweden, prostate cancer is the most common type of cancer among men. The care need within prostate cancer will get higher as the population increases and gets older. With this in mind, there is a need to streamline the care pathway. One way to do this is with a clinical decision support system. LÄS MER
4. Supervised Learning for Prediction of Tumour Mutational Burden
Master-uppsats, KTH/Matematisk statistikSammanfattning : Tumour Mutational Burden is a promising biomarker to predict response to immunotherapy. In this thesis, statistical methods of supervised learning were used to predict TMB: GLM, Decision Trees and SVM. LÄS MER
5. Segmentation and Prediction of Mutation Status of Malignant Melanoma Whole-slide Images using Deep Learning
Master-uppsats, Lunds universitet/Avdelningen för Biomedicinsk teknikSammanfattning : Malignant melanoma is an aggressive type of skin cancer. Gene mutations can make the disease progress faster, but specialised treatment exists. Today, gene mutations are detected with DNA-analysis which is costly and time-consuming. LÄS MER