Objective way to support embryo transfer: a probabilistic decision

Abstract

This study was supported by a grant, CTI Medtech Project Number: 9707.1 PFLS-L, Swiss Confederation. No competing interests are declared.

Factors predicting double embryo implantation following double embryo transfer in assisted reproductive technology: implications for elective single embryo transfer

“…Although impossible to study, it is certainly possible that if an embryo can survive until blastocyst stage for transfer, then the embryo is inherently of better quality, whereas some embryos that are transferred at cleavage stage may not have survived in culture until blastocyst stage and are of lower quality [21,27]. Additionally, having >10 oocytes retrieved compared to ≤10 oocytes retrieved with an average prognosis was independently predictive of double embryo implantation, which is also consistent with prior studies [13,14], but has not been shown Data are restricted to fresh, non-donor embryos. The results are of log-binomial regression.…”

“…Only a few small studies have examined factors associated with double embryo implantation following DET. Many of these studies showed that double embryo implantation was associated with younger age [12][13][14][15][16][17], a higher number of retrieved oocytes [12,13], and higher embryo quality [12,[15][16][17][18]. Given the limited information and small sample sizes on double embryo implantation following DET, we analyzed data from Centers for Disease Control and Prevention's (CDC's) National ART Surveillance System (NASS) to estimate the trends in rates of single embryo implantation following eSET and non-eSET, double embryo implantation following DET, triple embryo implantation following triplet embryo transfer (TET), and quadruple or higher embryo implantation following quadruple or higher embryo transfer (QET+), We assessed predictors of double embryo implantation following DET to further identify characteristics of potential good candidates for successful eSET.…”

A Bayesian network model for predicting pregnancy after in vitro fertilization

“…In a previous publication [14] we have introduced a novel probabilistic model of IVF transfers, which is a Bayesian network model based on the EU assumption. In [15] we have proposed a simple but effective averaging approach for estimating the parameters of the model from incomplete samples, which improves over the traditional MAP estimation.…”

Enabling pregnant women and their physicians to make informed medication decisions using artificial intelligence

“…Research in ART is represented well due to the fact that pharmacological intervention is necessary for several common ART practices. AI methods have been applied to inform and advise physicians [14], to predict pregnancy success [15][16][17][18], to provide optimized treatment [19], and to understand miscarriage risk [20].…”

“…Gianaroli et al conducted a retrospective study and proposed a Bayesian network (BN) model to predict occurrence of a pregnancy, and implantation status (i.e., no implantation, single implantation, and twin implantation) [16]. Variables considered and divided into categories for the model include the following: maternal age, previous IVF, intracytoplasmic sperm injection (ICSI) cycles, grade of each embryo, insemination technique, maternal/uterine receptivity, embryo viability, and pregnancy.…”