An Ontology for Clinical Decision Support System to Predict Female’s Fertile Period

Francisco Vaz, Rodrigo Rocha Silva, Jorge Bernardino

Abstract

Nowadays, many women do not fully realize what the fertile period is, as well as what it represents in their life. The prediction of fertile period is quite complex and difficult to calculate accurately and this is undoubtedly a problem for women’s. There are still some completely wrong ideas about reproductive health, especially about the fertile period and the menstrual cycle. A good example of the myths that persist is the fact that many women continue to believe that ovulation occurs precisely in the middle of their menstrual cycle, which is not always true. Therefore, to better understand the female cycle, we proposed a Clinical Decision Support System based on the use of an ontology. Our proposal can predict the female fertile period, based on certain factors that allow a calculation that is more accurate improving the quality of patient life.

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Paper Citation


in Harvard Style

Vaz F., Silva R. and Bernardino J. (2017). An Ontology for Clinical Decision Support System to Predict Female’s Fertile Period.In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, ISBN 978-989-758-272-1, pages 288-293. DOI: 10.5220/0006519102880293


in Bibtex Style

@conference{keod17,
author={Francisco Vaz and Rodrigo Rocha Silva and Jorge Bernardino},
title={An Ontology for Clinical Decision Support System to Predict Female’s Fertile Period},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD,},
year={2017},
pages={288-293},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006519102880293},
isbn={978-989-758-272-1},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD,
TI - An Ontology for Clinical Decision Support System to Predict Female’s Fertile Period
SN - 978-989-758-272-1
AU - Vaz F.
AU - Silva R.
AU - Bernardino J.
PY - 2017
SP - 288
EP - 293
DO - 10.5220/0006519102880293