Research Article
3P: Personalized Pregnancy Prediction in IVF Treatment Process
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@INPROCEEDINGS{10.1007/978-3-642-00413-1_7, author={Asli Uyar and H. Ciray and Ayse Bener and Mustafa Bahceci}, title={3P: Personalized Pregnancy Prediction in IVF Treatment Process}, proceedings={Electronic Healthcare. First International Conference, eHealth 2008, London, UK, September 8-9, 2008. Revised Selected Papers}, proceedings_a={E-HEALTH}, year={2012}, month={5}, keywords={In-vitro fertilization Embryo implantation prediction Classification Support vector machines}, doi={10.1007/978-3-642-00413-1_7} }- Asli Uyar
H. Ciray
Ayse Bener
Mustafa Bahceci
Year: 2012
3P: Personalized Pregnancy Prediction in IVF Treatment Process
E-HEALTH
Springer
DOI: 10.1007/978-3-642-00413-1_7
Abstract
We present an intelligent learning system for improving pregnancy success rate of IVF treatment. Our proposed model uses an SVM based classification system for training a model from past data and making predictions on implantation outcome of new embryos. This study employs an embryo-centered approach. Each embryo is represented with a data feature vector including 17 features related to patient characteristics, clinical diagnosis, treatment method and embryo morphological parameters. Our experimental results demonstrate a prediction accuracy of 82.7%. We have obtained the IVF dataset from Bahceci Women Health, Care Centre, in Istanbul, Turkey.
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