Computer Aided Breast Cancer Diagnosis
Abstract
While biopsy is a sensitive and specific test for breast cancer, to achieve a high sensitivity for cancer, many women with mammographic findings due to benign processes undergo biopsy. To improve the specificity of the decision to recommend biopsy and reduce the number of benign biopsies performed, a computer decision aid is being developed. ANN systems for prediction have been evaluated using a database of mammographic cases that were sent to biopsy with the results known. A case findings matching algorithm was implemented using a relational database to simplify and speed the coding. A Case-Based Reasoning approach was selected for this study since we wished to examine the cases and the similarity between them. To classify a given test case as benign or malignant, the case is compared to all previous cases, selecting those cases with were similar with regards to their findings. A decision variable was formed as the "malignancy ratio" computed as the ratio of the number of malignant cases to the total number of similar or "matched" cases. The system performed with an ROC area of 0.77. As described here, the system performs better than chance but poorer than the performance reported for radiologists on these data.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 1999
- Accession Number
- ADA383108
Entities
People
- Carey E. Floyd
Organizations
- Duke University