Aftificial Inteligence in Assisted Reproductive Techniques to Assess Oocyte Quality and Embryo Ploidy

The assisted reproduction success rate is affected by several factors including the age of the women, oocyte quality and maturation state, as well as sperm quality. Imaging of the meiotic spindle may be crucial for determining the oocyte maturation. Artificial intelligence (AI) will be applied to establish the complex oocyte quality, embryo ploidy and pregnancy success probability from the sequence of data, starting with the recording of the meiotic spindle in polarized light, through paternal factors up to the time lapse recording of early embryo development. This strategy should reduce the cost of fertility treatment thanks to increased efficiency in choosing the most promising candidates and reducing the need for costly laboratory analyses.

NCT Number	NCT06539104
Lead Sponsor	Charles University, Czech Republic Collaborators: Czech Academy of Sciences, Czech Technical University in Prague, General University Hospital, Prague
Conditions	Infertility, Infertility, Female, Infertility, Male, Infertility Unexplained
Enrollment	1,000 participants
Start Date	2024-01-05
Primary Completion	2027-12-31 (estimated)
Study Completion	2028-03-31 (estimated)
Updated on ClinicalTrials.gov	2025-01-22