Conference
Probabilistic Graphical Models and Deep Belief Networks for Prognosis of Breast Cancer
Abstract
We propose a probabilistic graphical model (PGM) for prognosis and diagnosis of breast cancer. PGMs are suitable for building predictive models in medical applications, as they are powerful tools for making decisions under uncertainty from big data with missing attributes and noisy evidence. Previous work relied mostly on clinical data to create a predictive model. Moreover, practical knowledge of an expert was needed to build the structure of …
Authors
Khademi M; Nedialkov NS
Pagination
pp. 727-732
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publication Date
December 1, 2015
DOI
10.1109/icmla.2015.196
Name of conference
2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA)