Harnessing Artificial Intelligence to Predict Ovarian Stimulation Outcomes in In Vitro Fertilization: Scoping Review.

ABSTRACT:

Background

In the realm of in vitro fertilization (IVF), artificial intelligence (AI) models serve as invaluable tools for clinicians, offering predictive insights into ovarian stimulation outcomes. Predicting and understanding a patient's response to ovarian stimulation can help in personalizing doses of drugs, preventing adverse outcomes (eg, hyperstimulation), and improving the likelihood of successful fertilization and pregnancy. Given the pivotal role of accurate predictions in IVF procedures, it becomes important to investigate the landscape of AI models that are being used to predict the outcomes of ovarian stimulation.

Objective

The objective of this review is to comprehensively examine the literature to explore the characteristics of AI models used for predicting ov

SUBMITTER: AlSaad R 

PROVIDER: S-EPMC11259766 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature