A novel computational analysis of heterogeneity in breast tissue

Susan Maskery*, Yonghong Zhang, Rick Jordan, Hai Hu, Craig Shriver, Jeffrey Hooke, Michael Liebman

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review


Breast cancer presents as part of a heterogeneous mix of breast disease pathologies whose biological origins are poorly understood. A systematic and quantitative study of heterogeneity in breast tissue would enable us to characterize the disease states present, and use that characterization to guide further research into the complex pathologic associations within breast tissue and between patients. Initially we focus on characterizing the co-occurrence of breast pathology-related diagnoses. In particular, this abstract presents our initial results from characterizing the co-occurrence of double and triple diagnoses. We will expand this analysis to co-occurrence of larger diagnosis sets. Additionally, we plan to analyze co-occurrence with other types of patient information, including: socio-economic status, family history, lifestyle choices, co-morbidity with other diseases, and many other factors hypothesized to contribute to an increased risk for developing breast cancer.

Original languageEnglish
Pages (from-to)395-400
Number of pages6
JournalProceedings of the IEEE Symposium on Computer-Based Medical Systems
StatePublished - 2005
Externally publishedYes
Event18th IEEE Symposium on Computer-Based Medical Systems - Dublin, Ireland, United Kingdom
Duration: 23 Jun 200524 Jun 2005


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