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Authors: Francisco Vaz 1 ; Rodrigo Rocha Silva 2 and Jorge Bernardino 3

Affiliations: 1 Polytechnic of Coimbra, ISEC, Rua Pedro Nunes, Coimbra and Portugal ; 2 FATEC Mogi das Cruzes, São Paulo State Technological College, Brazil, CISUC – Centre for Informatics and Systems of the University of Coimbra, Coimbra and Portugal ; 3 Polytechnic of Coimbra, ISEC, Rua Pedro Nunes, Coimbra, Portugal, CISUC – Centre for Informatics and Systems of the University of Coimbra, Coimbra and Portugal

Keyword(s): Data Mining, Fertile Period, Sharing Information, Application Architecture, Random Forest Algorithm.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Soft Computing ; Software Development ; Symbolic Systems

Abstract: There is a great need that many women have for a better calculation of the fertile period, since this calculation is important to know the best moments to have a sexual intercourse without pregnancy or with the intention of generating a pregnancy. This work describes the use of data mining of in development a mobile application for the calculation of the female fertile period. The application contains the main functionalities needed, such as the insertion of symptoms and moods each day, a calendar with daily events in which you can see the risk of pregnancy, ovulation day, among other features, taking into account all the necessary topics, such as the architecture, as well as the data mining using Random Forest algorithm and some of the main functionalities. The application allows the sharing of information with doctors and/or partners as well as a prediction of the probability of delay for the next menstrual cycle. These two features are completely innovative and will allow the succ ess of the application, through a greater number of downloads. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Vaz, F.; Silva, R. and Bernardino, J. (2018). Using Data Mining in a Mobile Application for the Calculation of the Female Fertile Period. In Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - KDIR; ISBN 978-989-758-330-8; ISSN 2184-3228, SciTePress, pages 359-366. DOI: 10.5220/0007228603590366

@conference{kdir18,
author={Francisco Vaz. and Rodrigo Rocha Silva. and Jorge Bernardino.},
title={Using Data Mining in a Mobile Application for the Calculation of the Female Fertile Period},
booktitle={Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - KDIR},
year={2018},
pages={359-366},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007228603590366},
isbn={978-989-758-330-8},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - KDIR
TI - Using Data Mining in a Mobile Application for the Calculation of the Female Fertile Period
SN - 978-989-758-330-8
IS - 2184-3228
AU - Vaz, F.
AU - Silva, R.
AU - Bernardino, J.
PY - 2018
SP - 359
EP - 366
DO - 10.5220/0007228603590366
PB - SciTePress