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.
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