Co-Occurrence Analysis for Discovery of Novel Breast Cancer Pathology Patterns

Autor: S. Maskery, Michael N. Liebman, Hai Hu, Jeffrey A. Hooke, Craig D. Shriver, Rick Jordan, Yonghong Zhang
Rok vydání: 2006
Předmět:
Zdroj: IEEE Transactions on Information Technology in Biomedicine. 10:497-503
ISSN: 1089-7771
DOI: 10.1109/titb.2005.863863
Popis: To discover novel patterns in pathology co-occurrence, we have developed algorithms to analyze and visualize pathology co-occurrence. With access to a database of pathology reports, collected under a single protocol and reviewed by a single pathologist, we can conduct an analysis greater in its scope than previous studies looking at breast pathology co-occurrence. Because this data set is unique, specialized methods for pathology co-occurrence analysis and visualization are developed. Primary analysis is through a co-occurrence score based on the Jaccard coefficient. Density maps are used to visualize global co-occurrence. When our co-occurrence analysis is applied to a population stratified by menopausal status, we can successfully identify statistically significant differences in pathology co-occurrence patterns between premenopausal and postmenopausal women. Genomic and proteomic experiments are planned to discover biological mechanisms that may underpin differences seen in pathology patterns between populations.
Databáze: OpenAIRE