J Appl Biomed 17:167-174, 2019 | DOI: 10.32725/jab.2019.015

Prediction of semen quality using artificial neural network

Anna Badura1,*, Urszula Marzec-Wróblewska1, Piotr Kamiński2,3, Paweł Łakota4,5, Grzegorz Ludwikowski6, Marek Szymański7,8, Karolina Wasilow8,9, Andżelika Lorenc1, Adam Buciński1
1 Nicolaus Copernicus University in Toruń, Collegium Medicum in Bydgoszcz, Faculty of Pharmacy, Department of Biopharmacy, Bydgoszcz, Poland
2 Nicolaus Copernicus University in Toruń, Collegium Medicum in Bydgoszcz, Faculty of Medicine, Department of Medical Biology and Biochemistry, Department of Ecology and Environmental Protection, Bydgoszcz, Poland
3 University of Zielona Góra, Faculty of Biological Sciences, Department of Biotechnology, Zielona Góra, Poland
4 University of Technology and Life Sciences, Faculty of Animal Biology, Department of Animal Biotechnology, Bydgoszcz, Poland
5 MAS, Poznań, Poland
6 Nicolaus Copernicus University in Toruń, Collegium Medicum in Bydgoszcz, Faculty of Health Sciences, Department of Obstetrics, Bydgoszcz, Poland
7 Nicolaus Copernicus University in Toruń, Collegium Medicum in Bydgoszcz, Faculty of Medicine, University Hospital No. 2, Department of Obstetrics, Female Pathology and Oncological Gynecology, Bydgoszcz, Poland
8 NZOZ Medical Center Genesis Infertility Treatment Clinic, Bydgoszcz, Poland
9 Nicolaus Copernicus University in Toruń, Collegium Medicum in Bydgoszcz, Faculty of Medicine, University Hospital No. 2, Family Medicine Clinic, Bydgoszcz, Poland

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.

Keywords: Artificial neural network; Concentration; Semen analysis; Semen characteristics; Spermatozoa
Conflicts of interest:

The authors have no conflict of interests to declare.

Received: December 11, 2018; Accepted: September 5, 2019; Prepublished online: September 17, 2019; Published: September 18, 2019  Show citation

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Badura A, Marzec-Wróblewska U, Kamiński P, Łakota P, Ludwikowski G, Szymański M, et al.. Prediction of semen quality using artificial neural network. J Appl Biomed. 2019;17(3):167-174. doi: 10.32725/jab.2019.015. PubMed PMID: 34907698.
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