Abstract
Breast cancer screening has reference to screening of asymptomatic, generally healthy women for breast cancer, to identify those who should receive a follow up check. Early screening can detect non-invasive ductal carcinoma in situ (called "pre breast cancer"), which almost never forms a lump and is generally non-detectible, except by mammography. This paper will describe the design and preliminary evaluation of this PNN/GRNN ensemble pre-screener, in the context of a possible pre-screening protocol, which may, if required, include other data. The results show that using the ensemble technique provides almost a 20% AUC increase over the average standalone PNN and almost 10% over the best performing PNN.
| Original language | English |
|---|---|
| Pages (from-to) | 438-443 |
| Number of pages | 6 |
| Journal | Procedia Computer Science |
| Volume | 12 |
| DOIs | |
| State | Published - 2012 |
| Event | 2012 Complex Adaptive Systems Conference - Washington, DC, United States Duration: Nov 14 2012 → Nov 16 2012 |
Keywords
- Bioinformatics
- Biomedical
- Breast cancer screening
- Statistical neural networks
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