Research Article
Bayesian Networks to Support the Management of Patients with ASCUS/LSIL Pap Tests
@INPROCEEDINGS{10.4108/icst.mobihealth.2014.257381, author={Panagiotis Bountris and Charalampos Tsirmpas and Maria Haritou and Abraham Pouliakis and Petros Karakitsos and Dimitrios Koutsouris}, title={Bayesian Networks to Support the Management of Patients with ASCUS/LSIL Pap Tests}, proceedings={4th International Conference on Wireless Mobile Communication and Healthcare - "Transforming healthcare through innovations in mobile and wireless technologies"}, publisher={IEEE}, proceedings_a={MOBIHEALTH}, year={2014}, month={12}, keywords={cervical cancer cytology human papillomavirus (hpv) bayesian networks risk assessment}, doi={10.4108/icst.mobihealth.2014.257381} }- Panagiotis Bountris
Charalampos Tsirmpas
Maria Haritou
Abraham Pouliakis
Petros Karakitsos
Dimitrios Koutsouris
Year: 2014
Bayesian Networks to Support the Management of Patients with ASCUS/LSIL Pap Tests
MOBIHEALTH
IEEE
DOI: 10.4108/icst.mobihealth.2014.257381
Abstract
In the majority of cases, cervical cancer (CxCa) develops as a result of underestimated abnormalities in the Pap test. Nowadays, there are ancillary molecular biology techniques providing important information related to CxCa and the Human Papillomavirus (HPV) natural history, including HPV DNA test, HPV mRNA tests and immunocytochemistry tests. However, these techniques have their own performance, advantages and limitations, thus a combinatorial approach via computational intelligence methods could exploit the benefits of each method and produce more accurate results. In this paper we present a risk assessment model based on a Bayesian Network which, by combining the results of Pap test and ancillary tests, may identify women at true risk of developing cervical cancer and support the management of patients with ASCUS or LSIL cytology. The model, following the paradigm of other implemented systems, can be integrated into existing platforms and be available on mobile terminals for anytime/anyplace medical consultation.
