AIMC Topic: Reproductive Techniques, Assisted

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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(+) ...

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...

[Application of Artificial Intelligence in Sperm Quality Analysis and Sperm Screening].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
Infertility is a global health issue, and more and more people are hoping to have babies by means of assisted reproductive technology. However, there are still many challenges in fertilization and pregnancy outcomes. Sperm quality is a key factor aff...

Moonshot. Long shot. Or sure shot. What needs to happen to realize the full potential of AI in the fertility sector?

Human reproduction (Oxford, England)
Quality healthcare requires two critical components: patients' best interests and best decisions to achieve that goal. The first goal is the lodestar, unchanged and unchanging over time. The second component is a more dynamic and rapidly changing par...

Infertility Treatment Now and in the Future.

Obstetrics and gynecology clinics of North America
Treatment of infertility has evolved as understanding of reproduction has improved. Fertility promoting surgery still is performed and recent advances have broken new ground. Hormonal treatments to correct gonadal dysfunction have been developed, but...