Classification of mouse sperm motility patterns using an automated multiclass support vector machines model.

ABSTRACT: Vigorous sperm motility, including the transition from progressive to hyperactivated motility that occurs in the female reproductive tract, is required for normal fertilization in mammals. We developed an automated, quantitative method that objectively classifies five distinct motility patterns of mouse sperm using Support Vector Machines (SVM), a common method in supervised machine learning. This multiclass SVM model is based on more than 2000 sperm tracks that were captured by computer-assisted sperm analysis (CASA) during in vitro capacitation and visually classified as progressive, intermediate, hyperactivated, slow, or weakly motile. Parameters associated with the classified tracks were incorporated into established SVM algorithms to generate a series of equations. These equations wer

SUBMITTER: Goodson SG 

PROVIDER: S-EPMC3099585 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature