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Due to the high variability in tumor morphology and the low signal-to-noise ratio inherent to mammography, manual classification of mammogram yields a significant number of patients being called back, and subsequent large number of biopsies performed to reduce the risk of missing cancer. The convolutional neural network (CNN) is a popular deep-learning construct used in image classification. This...
Glioblastoma multiforme (GBM) is the most fatal malignant type of brain tumor with a very poor prognosis with a median survival of around one year. Numerous studies have reported tumor subtypes that consider different characteristics on individual patients, which may play important roles in determining the survival rates in GBM. In this study, we present a pathway-based clustering method using Restricted...
This paper proposes a novel approach to select features that are jointly predictive of survival times and classification within subgroups. Both tasks are common but generally tackled independently in clinical data analysis. Here we propose an embedded feature selection to select common markers, i.e. genes, for both tasks seen as a multi-objective optimization. The Coxlogit model relies on a Cox proportional...
Our Genomic Relevance Parameterization (GReP) model aims to explore a possible relationship between gene expression values from breast cancer patients and mathematical tumor growth modeling parameters calculated using data from clinical and preclinical measurements. We introduce two methods to relate genomic information and the tumor growth measurements. One method explores the impact of exponentiation...
This paper investigates the use of neural networks to detect and locate early breast cancer using a simple feed-forward back-propagation neural network. In order to test the proposed algorithm, an electromagnetic simulator is used to build a three-dimensional breast model. Spherical tumors of radii 1 mm, 2 mm, 4 mm, and 5 mm are assumed to be at different locations in the breast model. An ultra-wideband...
Identification of genes and pathways involving in diseases and physiological conditions is a major task in systems biology. In this study, we develop a new non-parameter Ising model to integrate protein-protein interaction network and microarray data for identifying differentially expressed (DE) genes. We also propose a simulated annealing algorithm to find the optimal configuration of the Ising model...
Maintaining the financial sustainability of healthcare provision makes developments in e-systems of the utmost priority in healthcare. In particular, it leads to a radical review of healthcare delivery for the future as personalised, preventive, predictive and participatory, or p-Health. It is a vision that places e-systems at the core of healthcare delivery, in contrast to current practice . This...
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