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Classification Of Breast Cancer Nottingham Prognostic Index Using High-Dimensional Embedding And Convolutional Neural Networks, Li Zhou
Electronic Theses and Dissertations
This work builds a prediction model for multi-omics breast cancer Nottingham Prognostics Index (NPI) classes. Rapid development in next-generation sequencing led to the ability to measure different biological indicators called multi-omics data. The availability of multi-omics data sparked the challenge of integrating and analyzing these various biological measures to understand the progression of the diseases. High-dimensional embedding techniques are used to present the features in the lower dimension, that is a 2-dimensional map. This thesis presents a supervised learning method used to predict breast cancer NPI. The objectives of this research are (i) build a diagnosis system for breast cancer …
Deep Learning Applications In Medical Bioinformatics, Ziad Omar
Deep Learning Applications In Medical Bioinformatics, Ziad Omar
Electronic Theses and Dissertations
After a patient’s breast cancer diagnosis, identifying breast cancer lymph node metastases is one of the most important and critical factor that is directly related to the patient’s survival. The traditional way to examine the existence of cancer cells in the breast lymph nodes is through a lymph node procedure, biopsy. The procedure process is time-consuming for the patient and the provider, costly, and lacks accuracy as not every lymph node is examined. The intent of this study is to develop an artificial neural network (ANNs) that would map genetic biomarkers to breast lymph node classes using ANNs. The neural …