Deep learning early warning system for embryo culture conditions and embryologist performance in the ART laboratory

The human factor: does the operator performing the embryo transfer significantly impact the cycle outcome?

(2020) F Cirillo et al.   HUMAN REPRODUCTION

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

(2019) Carol Lynn Curchoe et al.   JOURNAL OF ASSISTED REPRODUCTION AND GENETICS

Deep learning as a predictive tool for fetal heart pregnancy following time-lapse incubation and blastocyst transfer

(2019) D Tran et al.   HUMAN REPRODUCTION

An artificial neural network for the prediction of assisted reproduction outcome

(2019) Paraskevi Vogiatzi et al.   JOURNAL OF ASSISTED REPRODUCTION AND GENETICS

Tracking quality: can embryology key performance indicators be used to identify clinically relevant shifts in pregnancy rate?

(2018) Elizabeth R Hammond et al.   HUMAN REPRODUCTION

The Vienna consensus: report of an expert meeting on the development of ART laboratory performance indicators

(2017)   REPRODUCTIVE BIOMEDICINE ONLINE

‘By the work, one knows the workman’: the practice and profession of the embryologist and its translation to quality in the embryology laboratory

(2015) Kathryn J. Go   REPRODUCTIVE BIOMEDICINE ONLINE

Rethinking In Vitro Embryo Culture: New Developments in Culture Platforms and Potential to Improve Assisted Reproductive Technologies1

(2011) Gary D. Smith et al.   BIOLOGY OF REPRODUCTION