AIMC Topic: Fertilization in Vitro

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A hybrid artificial intelligence model leverages multi-centric clinical data to improve fetal heart rate pregnancy prediction across time-lapse systems.

Human reproduction (Oxford, England)
STUDY QUESTION: Can artificial intelligence (AI) algorithms developed to assist embryologists in evaluating embryo morphokinetics be enriched with multi-centric clinical data to better predict clinical pregnancy outcome?

Embryologist agreement when assessing blastocyst implantation probability: is data-driven prediction the solution to embryo assessment subjectivity?

Human reproduction (Oxford, England)
STUDY QUESTION: What is the accuracy and agreement of embryologists when assessing the implantation probability of blastocysts using time-lapse imaging (TLI), and can it be improved with a data-driven algorithm?

Artificial intelligence model to predict pregnancy and multiple pregnancy risk following in vitro fertilization-embryo transfer (IVF-ET).

Taiwanese journal of obstetrics & gynecology
OBJECTIVE: To decrease multiple pregnancy risk and sustain optimal pregnancy chance by choosing suitable number of embryos during transfer, this study aims to construct artificial intelligence models to predict the pregnancy outcome and multiple preg...

Impact of oocyte donor age and breed on embryo production in cattle, and relationship of dairy and beef embryo recipients on pregnancy and the subsequent performance of offspring: A review.

Reproduction, fertility, and development
Genomic selection combined with in vitro embryo production (IVEP) with oocytes from heifer calves provides a powerful technology platform to reduce generation interval and significantly increase the rate of genetic gain in cattle. The ability to obta...

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...

Unsupervised Deep Learning based Longitudinal Follicular Growth Tracking during IVF Cycle using 3D Transvaginal Ultrasound in Assisted Reproduction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Longitudinal follicle tracking is needed in clinical practice for diagnosis and management in assisted reproduction. Follicles are tracked over the in-vitro fertilization (IVF) cycle, and this analysis is usually performed manually by a medical pract...

Consensus vision.

Fertility and sterility
The goal of this Views and Interviews series was to bring together the thought leaders in the field and envision what the laboratory will look like in the future. This consensus piece strives to take the thoughts of those leaders and develop themes a...

A preliminary study of sperm identification in microdissection testicular sperm extraction samples with deep convolutional neural networks.

Asian journal of andrology
Sperm identification and selection is an essential task when processing human testicular samples for in vitro fertilization. Locating and identifying sperm cell(s) in human testicular biopsy samples is labor intensive and time consuming. We developed...

Predictive modeling in reproductive medicine: Where will the future of artificial intelligence research take us?

Fertility and sterility
Artificial intelligence (AI) systems have been proposed for reproductive medicine since 1997. Although AI is the main driver of emergent technologies in reproduction, such as robotics, Big Data, and internet of things, it will continue to be the engi...