Abstract
This paper show a computational tool that allow the analysis of the information obtained from a database that contains features of the fine needle aspiration (FNA) procedure, whose goal is to diagnose breast masses applying artificial intelligence. The methodology include the recollection of data, process of cleaning, neural networks and Bayesian’s networks for prediction of the data, evaluation and comparison.
Supported by Universidad de La Salle.
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Lancheros-Cuesta, D., Bustos, J.C., Rubiano, N., Tumialan, A. (2022). Artificial Intelligence for Prevention of Breast Cancer. In: Figueroa-García, J.C., Franco, C., Díaz-Gutierrez, Y., Hernández-Pérez, G. (eds) Applied Computer Sciences in Engineering. WEA 2022. Communications in Computer and Information Science, vol 1685. Springer, Cham. https://doi.org/10.1007/978-3-031-20611-5_9
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