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Prediction of semen quality using artificial neural network
Anna Badura, Urszula Marzec-Wróblewska, Piotr Kamiński, Paweł Łakota, Grzegorz Ludwikowski, Marek Szymański, Karolina Wasilow, Andżelika Lorenc, Adam Buciński
Language English Country Czech Republic
- MeSH
- Semen Analysis * methods instrumentation MeSH
- Humans MeSH
- Sperm Motility MeSH
- Infertility, Male MeSH
- Neural Networks, Computer * MeSH
- Sperm Count methods instrumentation MeSH
- Surveys and Questionnaires MeSH
- Semen * MeSH
- Sperm Banks MeSH
- Spermatozoa * abnormalities growth & development ultrastructure MeSH
- Check Tag
- Humans MeSH
Examination of semen characteristics is routinely performed for fertility status investigation of the male partner of an infertile couple as well as for evaluation of the sperm donor candidate. A useful tool for preliminary assessment of semen characteristics might be an artificial neural network. Thus, the aim of the present study was to construct an artificial neural network, which could be used for predicting the result of semen analysis based on the basic questionnaire data. On the basis of eleven survey questions two models of artificial neural networks to predict semen parameters were developed. The first model aims to predict the overall performance and profile of semen. The second network was developed to predict the concentration of sperm. The network to evaluate sperm concentration proved to be the most efficient. 92.93% of the patients in the learning process were properly qualified for the group with a correct or incorrect result, while the result for the test set was 85.71%. This study suggests that an artificial neural network based on eleven survey questions might be a valuable tool for preliminary evaluation and prediction of the semen profile.
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Literatura
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