Infertility is a disease according to the WHO, affecting 1 in 6 couples. In vitro fertilization (IVF) is a rapidly evolving technology that has been used for the treatment of human infertility for over 40 years, with over 8 million babies born worldwide.
IVF outcome depends on complex interactions of numerous patient and treatment-related parameters. A wealth of IVF data is exponentially accumulated. As a result, we have the opportunity, but also the challenge, to analyse these "big IVF data" to make predictions, facilitate clinical decisions and tailor fertility treatment.
We are developing "IVF Insight", an AI-powered application to rapidly inform clinical decisions and make comprehensive predictions of fertility treatment. The application will be based on extensive data collected from infertility patients in order to createdetailed unique patient profiles. We will achieve this by using DNN to analyse key digital data collected from electronic patient records, wearable devices, genomic analysis and automated embryo imaging.
Our DNN application, IVF insight, will provide fertility experts with estimates of the chance of successful pregnancy and live birth, but also of adverse events, such as miscarriage, multiple pregnancy or birth defects in the offspring.
In addition, IVFinsight will facilitate informed decisions from the early pretreatment stages, through to the choice of the best drug regime, method of egg fertilisation and duration of culture, until the selection of the best embryos for transfer or cryopreservation.
IVFinsight will advance the clinical decision-making process, improve patient experience through more accurate counseling, provide cost efficiency, and boost success rates by identifying optimal personalised treatment pathways.