*Author details available on the publication
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?
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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