Prediction Models for Polycystic Ovary Syndrome Using Data Mining

AuthID
 P-00T-RJK
5
Author(s)
Neto, C
·
Silva, M
·
Fernandes, M
·
Ferreira, D
·
1
Editor(es)
Antipova,T
Tipo de Documento
Proceedings Paper
Year published
2021
Publicado
in Advances in Intelligent Systems and Computing, ISSN: 2194-5357
Volume: 1352, Páginas: 210-221
Conference
International Conference on Advances in Digital Science, Icads 2021, Date: 19 February 2021 through 21 February 2021
Indexing
Scopus®
Crossref®6
Google Scholar®
Publication Identifiers
SCOPUS: 2-s2.0-85103521052
Source Identifiers
ISSN: 2194-5357
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