Application of gene expression programming and neural networks to predict adverse events of radical hysterectomy in cervical cancer patients

The aim of this article was to compare gene expression programming (GEP) method with three types of neural networks in the prediction of adverse events of radical hysterectomy in cervical cancer patients. One-hundred and seven patients treated by radical hysterectomy were analyzed. Each record repre...

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Detalles Bibliográficos
Autores principales: Kusy, Maciej, Obrzut, Bogdan, Kluska, Jacek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2013
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3825140/
https://www.ncbi.nlm.nih.gov/pubmed/24136688
http://dx.doi.org/10.1007/s11517-013-1108-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3825140/
https://www.ncbi.nlm.nih.gov/pubmed/24136688
http://dx.doi.org/10.1007/s11517-013-1108-8

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