Improving breast cancer outcome prediction by combining multiple data sources

Cancer has recently become the number one cause of death in The Netherlands. Breast cancer is the most prevalent form of cancer among females, with a lifetime risk of 12.8% (i.e. the 1 in 8 rule). As a result, more and more research is devoted to getting a better insight into cancer, and to further develop strategies for personalized treatment....

A comparison of supervised gene set searching algorithms for outcome prediction of breast cancer

Determining whether a tumor is likely to metastasize is a task that helps selecting the correct treatment for a patient. In breast cancer research, traditional classification of tumors depends on evaluating clinical risk factors, which has led to over-treatment in thepast. High-throughput technologies such as mRNA microarrays have generated...

Supervised classification and spatial dependency analysis in human cancer using high throughput data

Clinical study for classification of benign, dysplastic, and malignant oral lesions using autofluorescence spectroscopy