Are computational applications the "crystal ball" in the IVF laboratory? The evolution from mathematics to artificial intelligence

Abstract

Mathematics rules the world of science. Innovative technologies based on mathematics have paved the way for implementation of novel strategies in assisted reproduction. Ascertaining efficient embryo selection in order to secure optimal pregnancy rates remains the focus of the in vitro fertilization scientific community and the strongest driver behind innovative approaches. This scoping review aims to describe and analyze complex models based on mathematics for embryo selection, devices, and software most widely employed in the IVF laboratory and algorithms in the service of the cutting-edge technology of artificial intelligence. Despite their promising nature, the practicing embryologist is the one ultimately responsible for the success of the IVF laboratory and thus the one to approve embracing pioneering technologies in routine practice. Applied mathematics and computational biology have already provided significant insight into the selection of the most competent preimplantation embryo. This review describes the leap of evolution from basic mathematics to bioinformatics and investigates the possibility that computational applications may be the means to foretell a promising future for the IVF clinical practice.

Keywords: Artificial intelligence IVF; Bayesian models IVF; Devices IVF; Prediction models IVF; Time-lapse IVF.

Fig. 1

Outline of sophisticated models and software employed in the IVF laboratory and analyzed in this review

Fig. 2

Goodness-of-fit as measured by area under the curve (AUC) for the four prediction models types that include two or more algorithms: artificial intelligence, Bayesian classifiers, time-lapse (TL) on euploidy, and time-lapse (TL) on morphokinetics