Non-invasive prediction of human embryonic ploidy using artificial intelligence: a systematic review and meta-analysis.

ABSTRACT:

Background

Embryonic ploidy is critical for the success of embryo transfer. Currently, preimplantation genetic testing for aneuploidy (PGT-A) is the gold standard for detecting ploidy abnormalities. However, PGT-A has several inherent limitations, including invasive biopsy, high economic burden, and ethical constraints. This paper provides the first comprehensive systematic review and meta-analysis of the performance of artificial intelligence (AI) algorithms using embryonic images for non-invasive prediction of embryonic ploidy.

Methods

Comprehensive searches of studies that developed or utilized AI algorithms to predict embryonic ploidy from embryonic imaging, published up until August 10, 2024, across PubMed, MEDLINE, Embase, IEEE, SCOPUS, Web of Science, and the Cochrane

SUBMITTER: Xin X 

PROVIDER: S-EPMC11541425 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature