• Authors*

Léna Bardet, Jean-Baptiste Excoffier, Noemie Salaun-Penquer, Matthieu Ortala, Maud Pasquier, Emmanuelle Mathieu d'Argent, Nathalie Massin 

*Author details available on the publication

• Reference

Published:March 31, 2022DOI:https://doi.org/10.1016/j.rbmo.2022.03.020

Research question
Can a machine learning model better predict the cumulative live birth rate for a couple after intrauterine insemination or embryo transfer than Cox regression based on their personal characteristics?

Discussion :

Explicability-based methods would allow access to new knowledge, to gain a greater comprehension of which characteristics and interactions really influence a couple's journey.

These models can be used by practitioners and patients to make better informed decisions about performing ART.

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