Machine-intelligence for developing a potent signature to predict ovarian response to tailor assisted reproduction technology
Sisi Yan, Wenyi Jin, Jinli Ding, Tailang Yin, Yi Zhang, Jing Yang
Abstract
level and follicle number on hCG day, which provides important theoretical guidance and experimental data for further application. Generally, the CPLM and HPTM can offer effective POR prediction for patients who are receiving assisted reproduction technology (ART), and has great potential for guiding the clinical treatment of infertility.
Topics & Concepts
ReproductionComputer scienceSignature (topology)Artificial intelligenceBiologyMathematicsEcologyGeometryOvarian function and disordersReproductive Biology and FertilityGenetic and phenotypic traits in livestock