CASAnova: a multiclass support vector machine model for the classification of human sperm motility patterns.

ABSTRACT: The ability to accurately monitor alterations in sperm motility is paramount to understanding multiple genetic and biochemical perturbations impacting normal fertilization. Computer-aided sperm analysis (CASA) of human sperm typically reports motile percentage and kinematic parameters at the population level, and uses kinematic gating methods to identify subpopulations such as progressive or hyperactivated sperm. The goal of this study was to develop an automated method that classifies all patterns of human sperm motility during in vitro capacitation following the removal of seminal plasma. We visually classified CASA tracks of 2817 sperm from 18 individuals and used a support vector machine-based decision tree to compute four hyperplanes that separate five classes based on their kinematic

SUBMITTER: Goodson SG 

PROVIDER: S-EPMC6248632 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature