AIMC Topic: Reproductive Techniques, Assisted

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Artificial intelligence and machine learning for human reproduction and embryology presented at ASRM and ESHRE 2018.

Journal of assisted reproduction and genetics
Sixteen artificial intelligence (AI) and machine learning (ML) approaches were reported at the 2018 annual congresses of the American Society for Reproductive Biology (9) and European Society for Human Reproduction and Embryology (7). Nearly every as...

Fitting the data from embryo implantation prediction: Learning from label proportions.

Statistical methods in medical research
Machine learning techniques have been previously used to assist clinicians to select embryos for human-assisted reproduction. This work aims to show how an appropriate modeling of the problem can contribute to improve machine learning techniques for ...

Insulin improves in vitro survival of equine preantral follicles enclosed in ovarian tissue and reduces reactive oxygen species production after culture.

Theriogenology
This study investigated the effect of insulin concentration on the in vitro culture of equine preantral follicles enclosed in ovarian tissue. Ovarian tissue samples were immediately fixed (noncultured control) or cultured for 1 or 7 days in α-MEM(+) ...

An intelligent decision-making system for embryo transfer in reproductive technology: a machine learning-based approach.

Systems biology in reproductive medicine
Infertility has emerged as a significant public health concern, with assisted reproductive technology (ART) is a last-resort treatment option. However, ART's efficacy is limited by significant financial cost and physical discomfort. The aim of this s...

Comparative reproductive biology, advances in reproductive health, and cultivating inclusion in the scientific community: highlights from the 2024 Annual Meeting of the Society for Reproductive Biology.

Reproduction, fertility, and development
In 2024, the reproductive biology research community in Australia and New Zealand reunited in Adelaide for the Society for Reproductive Biology (SRB) Annual Meeting. The conference showcased major advances made in key areas of reproductive biology, w...

Deep learning classification integrating embryo images with associated clinical information from ART cycles.

Scientific reports
An advanced Artificial Intelligence (AI) model that leverages cutting-edge computer vision techniques to analyse embryo images and clinical data, enabling accurate prediction of clinical pregnancy outcomes in single embryo transfer procedures. Three ...

Artificial intelligence in assisted reproductive technology: separating the dream from reality.

Reproductive biomedicine online
This paper critically reviews the role of artificial intelligence (AI) in assisted reproductive technology (ART), a nascent field that has emerged over the last decade. While AI holds immense promise for enhancing IVF efficiency, standardization, and...

Ethics of artificial intelligence in embryo assessment: mapping the terrain.

Human reproduction (Oxford, England)
Artificial intelligence (AI) has the potential to standardize and automate important aspects of fertility treatment, improving clinical outcomes. One promising application of AI in the fertility clinic is the use of machine learning (ML) tools to ass...

Artificial intelligence and assisted reproductive technology: A comprehensive systematic review.

Taiwanese journal of obstetrics & gynecology
The objective of this review is to evaluate the contributions of Artificial Intelligence (AI) to Assisted Reproductive Technologies (ART), focusing on its role in enhancing the processes and outcomes of fertility treatments. This study analyzed 48 re...