Embryo evaluation and selection embody the aggregate manifestation of the entire in vitro
fertilization (IVF) process. It aims to choose the “best” embryos from the larger cohort of …

In recent years, the amount of data produced in the field of ART has increased exponentially.
The diversity of data is large, ranging from videos to tabular data. At the same time, artificial …

In vitro fertilization has been regarded as a forefront solution in treating infertility for over four
decades, yet its effectiveness has remained relatively low. This could be attributed to the …

Human infertility is a major global public health issue estimated to affect one out of six
couples, while the number of assisted reproduction cycles grows impressively year over …

Purpose Our retrospective study is to investigate an end-to-end deep learning model in
identifying ploidy status through raw time-lapse video. Methods By randomly dividing the …

Background Infertility is a significant problem of humanity. In vitro fertilisation is one of the
most effective and frequently applied ART methods. The effectiveness IVF depends on the …

With the exponential growth of computing power and accumulation of embryo image data in
recent years, artificial intelligence (AI) is starting to be utilized in embryo selection in IVF …

The use of time lapse systems (TLS) in In Vitro Fertilization (IVF) labs to record developing
embryos has paved the way for deep-learning based computer vision algorithms to assist …

Purpose Our objective was to design an automated deep learning model that extracts the
morphokinetic events of embryos that were recorded by time-lapse incubators. Using …

Gamete and embryo quality are critical to the success rate of Assisted Reproductive
Technology (ART) cycles, but there remains a lack of methods to accurately measure the …