Artificial intelligence in reproductive medicine
R Wang, W Pan, L **, Y Li, Y Geng, C Gao… - …, 2019 - rep.bioscientifica.com
Artificial intelligence (AI) has experienced rapid growth over the past few years, moving from
the experimental to the implementation phase in various fields, including medicine …
the experimental to the implementation phase in various fields, including medicine …
Advances in sperm analysis: techniques, discoveries and applications
Infertility affects one in six couples worldwide, and fertility continues to deteriorate globally,
partly owing to a decline in semen quality. Sperm analysis has a central role in diagnosing …
partly owing to a decline in semen quality. Sperm analysis has a central role in diagnosing …
A machine learning approach for prediction of pregnancy outcome following IVF treatment
Infertility affects one out of seven couples around the world. Therefore, the best possible
management of the in vitro fertilization (IVF) treatment and patient advice is crucial for both …
management of the in vitro fertilization (IVF) treatment and patient advice is crucial for both …
[HTML][HTML] Prediction of implantation after blastocyst transfer in in vitro fertilization: a machine-learning perspective
Objective To develop a random forest model (RFM) to predict implantation potential of a
transferred embryo and compare it with a multivariate logistic regression model (MvLRM) …
transferred embryo and compare it with a multivariate logistic regression model (MvLRM) …
Comparative study of machine learning approaches integrated with genetic algorithm for IVF success prediction
Introduction IVF is a widely-used assisted reproductive technology with a consistent success
rate of around 30%, and improving this rate is crucial due to emotional, financial, and health …
rate of around 30%, and improving this rate is crucial due to emotional, financial, and health …
[HTML][HTML] A review of machine learning approaches in assisted reproductive technologies
Aim: This review provides an overview on machine learning–based prediction models in
ART. Methods: This article was executed based on a literature review through scientific …
ART. Methods: This article was executed based on a literature review through scientific …
Using feature optimization and LightGBM algorithm to predict the clinical pregnancy outcomes after in vitro fertilization
L Li, X Cui, J Yang, X Wu, G Zhao - Frontiers in endocrinology, 2023 - frontiersin.org
Background According to a recent report by the WHO, approximately 17.5\%(about one-
sixth) of the global adult population is affected by infertility. Consequently, researchers …
sixth) of the global adult population is affected by infertility. Consequently, researchers …
Machine learning vs. classic statistics for the prediction of IVF outcomes
Purpose To assess whether machine learning methods provide advantage over classic
statistical modeling for the prediction of IVF outcomes. Methods The study population …
statistical modeling for the prediction of IVF outcomes. Methods The study population …
Internal validation and comparison of predictive models to determine success rate of infertility treatments: a retrospective study of 2485 cycles
Infertility is a significant health problem and assisted reproductive technologies to treat
infertility. Despite all efforts, the success rate of these methods is still low. Also, each of these …
infertility. Despite all efforts, the success rate of these methods is still low. Also, each of these …
[HTML][HTML] Factors associated with in vitro fertilization live birth outcome: A comparison of different classification methods
P Amini, F Ramezanali… - … Journal of Fertility & …, 2021 - ncbi.nlm.nih.gov
Background In vitro fertilization (IVF) is a useful assisted reproductive technology to achieve
pregnancy in infertile couples. However, it is very important to optimize the success rate after …
pregnancy in infertile couples. However, it is very important to optimize the success rate after …