EFRE 40: An AI-generated predictive algorithm for IVF success in AMA

Document Type : Debate

Authors

1 Obstetrics and Gynecology Department, Faculty of Medicine, Alexandria University, Egypt.

2 Egyptian Foundation of Reproductive Medicine and Embryology (EFRE), Egypt.

3 Madina Fertility Center, Madina Women's Hospital, Alexandria, Egypt.

4 Dar Alteb Infertility Center, Alexandria, Egypt.

5 Electrical engineering department, faculty of engineering Alexandria, Egypt

Abstract

Natural Language Processing (NLP), a subset of artificial intelligence (AI), enables computers to interpret and generate human language. Machine learning (ML) models are increasingly employed to analyze clinical, hormonal, and embryological data to predict in vitro fertilization (IVF) success rates.the success rates of IVF, particularly among women over the age of 40, remain a significant concern. Advancements in artificial intelligence (AI) offer promising avenues to enhance predictive modeling in this domain, potentially improving clinical outcomes This study aims to develop a predictive model using Meta AI to estimate live birth probabilities in women over 40 undergoing IVF. By inputting specific variables into the AI model, we seek to create a tool that can assist clinicians and patients in making informed decisions about fertility treatments, ultimately improving personalized care in this demographic. The model was created using a theoretical framework, without real-world patient data. The model included; embryo quality, uterine receptivity, maternal age, sperm quality and previuos pregnancy outcome. The aim of the model is to predict clinical pregnency rate and live birth rate.

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Journal of Reproductive Medicine and Embryology
Volume 1, Issue 4
February 2025
Pages 276-285

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