Validation of artificial neural network models for predicting biochemical markers associated with male infertility.

Unlabelled: Seminal fluid is the secretion from many glands comprised of several organic and inorganic compounds including free amino acids, proteins, fructose, glucosidase, zinc, and other scavenging elements like Mg(2+), Ca(2+), K(+), and Na(+). Therefore, in the view of development of novel approaches and proper diagnosis to male infertility, overall understanding of the biochemical and molecular composition and its role in regulation of sperm quality is highly desirable. Perhaps this can be achieved through artificial intelligence.

EFFECTS OF VARIOUS SEMEN EXTENDERS ON SEMEN PARAMETERS FOR THE PURPOSE OF HUMAN MALE FERTILITY PRESERVATION.

Background: Cryopreservation enables semen to be preserved at subzero temperatures, usually at -196 degrees C. There is a need in preparing good extender for the semen to be cryopreserved until use, especially in the field of assisted reproduction.

Objective: To elucidate the apt extender for preserving both infertile and fertile samples for a minimum period and to check the post thaw results for various extenders used.

Prediction of Zn concentration in human seminal plasma of Normospermia samples by Artificial Neural Networks (ANN).

Purpose: There has been an increasing interest in the evaluation of metal ion concentration, present in different body fluids. It is known that metal ions, especially zinc play vital role in the fertility of human semen.

Objective: The main objective of the study is to evaluate the Zn concentration in Normospermia samples by Atomic absorption spectroscopy (AAS) and to predict the same by artificial neural network (ANN).