Anna Badura, Urszula Marzec-Wroblewska, Piotr Kaminski, Pawel Lakota, Grzegorz Ludwikowski, Marek Szymanski, Karolina Wasilow, Andzelika Lorenc, Adam Bucinski
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引用次数: 8
Abstract
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.
期刊介绍:
Journal of Applied Biomedicine promotes translation of basic biomedical research into clinical investigation, conversion of clinical evidence into practice in all medical fields, and publication of new ideas for conquering human health problems across disciplines.
Providing a unique perspective, this international journal publishes peer-reviewed original papers and reviews offering a sensible transfer of basic research to applied clinical medicine. Journal of Applied Biomedicine covers the latest developments in various fields of biomedicine with special attention to cardiology and cardiovascular diseases, genetics, immunology, environmental health, toxicology, neurology and oncology as well as multidisciplinary studies. The views of experts on current advances in nanotechnology and molecular/cell biology will be also considered for publication as long as they have a direct clinical impact on human health. The journal does not accept basic science research or research without significant clinical implications. Manuscripts with innovative ideas and approaches that bridge different fields and show clear perspectives for clinical applications are considered with top priority.