Neural networks approach to early breast cancer detection
| Autor: | Ana Jovicevic Bekic, Drasko Furundzic, Miodrag Djordjevic |
|---|---|
| Rok vydání: | 1998 |
| Předmět: |
Early breast cancer detection
Computer science 02 engineering and technology Machine learning computer.software_genre 03 medical and health sciences 0302 clinical medicine Breast cancer 0202 electrical engineering electronic engineering information engineering medicine Risk factor Set (psychology) Selection (genetic algorithm) Artificial neural network business.industry Healthy population medicine.disease 3. Good health Identification (information) Hardware and Architecture 020201 artificial intelligence & image processing Artificial intelligence business computer 030217 neurology & neurosurgery Software |
| Zdroj: | Journal of Systems Architecture. 44:617-633 |
| ISSN: | 1383-7621 |
| DOI: | 10.1016/s1383-7621(97)00067-2 |
| Popis: | Efficient prevention is strongly correlated with an early detection of breast cancer. The common effort of many researchers in this field resulted in the selection of the most prominent risk factors related to breast cancer. In this paper we present a neural network based model for the efficient automated identification of women at high risk of developing breast cancer from a wide, healthy population on the basis of data, referring to a properly selected set of risk factors and symptoms. Using this model we achieved a highly accurate classification and also the initial set of features reduction. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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