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419975

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

Article

Last updated: 09 Apr 2025

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Subjects

-

Tags

Assisted reproduction

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.

DOI

10.21608/jrme.2025.369219.1035

Keywords

Prediction Models, advanced maternal age, artificial intelligence

Authors

First Name

Hassan

Last Name

Maghraby

MiddleName

-

Affiliation

Obstetrics and Gynecology Department, Faculty of Medicine, Alexandria University, Egypt., Egyptian Foundation of Reproductive Medicine and Embryology (EFRE), Egypt.

Email

hassanmaghraby@gmail.com

City

-

Orcid

0000-0003-3661-1594

First Name

Sherif

Last Name

Gaafar

MiddleName

-

Affiliation

Obstetrics and Gynecology Department, Faculty of Medicine, Alexandria University, Egypt., Egyptian Foundation of Reproductive Medicine and Embryology (EFRE), Egypt., Madina Fertility Center, Madina Women's Hospital, Alexandria, Egypt.

Email

shgaafar301@yahoo.com

City

-

Orcid

-

First Name

Ashraf

Last Name

Abo Ali

MiddleName

-

Affiliation

Egyptian Foundation of Reproductive Medicine and Embryology (EFRE), Egypt., Madina Fertility Center, Madina Women's Hospital, Alexandria, Egypt.

Email

aboalimadinahospital@gmail.com

City

-

Orcid

-

First Name

Mohamed

Last Name

Elmahdy

MiddleName

-

Affiliation

Obstetrics and Gynecology Department, Faculty of Medicine, Alexandria University, Egypt., Egyptian Foundation of Reproductive Medicine and Embryology (EFRE), Egypt.

Email

mahdy_moh@yahoo.com

City

-

Orcid

0000-0003-4332-9845

First Name

Nehal

Last Name

Adel

MiddleName

-

Affiliation

Egyptian Foundation of Reproductive Medicine and Embryology (EFRE), Egypt., Madina Fertility Center, Madina Women's Hospital, Alexandria, Egypt.

Email

nehal_adel83@hotmail.com

City

Alexandria

Orcid

0000-0002-2853-8334

First Name

Heba

Last Name

Hassan

MiddleName

-

Affiliation

Egyptian Foundation of Reproductive Medicine and Embryology (EFRE), Egypt., Dar Alteb Infertility Center, Alexandria, Egypt.

Email

hebahali85@gmail.com

City

-

Orcid

-

First Name

Rana

Last Name

Fawzy

MiddleName

-

Affiliation

Electrical engineering department, faculty of engineering Alexandria, Egypt

Email

rana.fawzy@ericsson.com

City

-

Orcid

-

Volume

1

Article Issue

4

Related Issue

54794

Issue Date

2025-02-01

Receive Date

2025-03-18

Publish Date

2025-02-01

Page Start

276

Page End

285

Online ISSN

3009-7282

Article File

JRME_Volume 1_Issue 4_Pages 276-285.pdf

PDF . 375.8kB

Link

https://jrme.journals.ekb.eg/article_419975.html

Detail API

http://journals.ekb.eg?_action=service&article_code=419975

Order

10

Type

Debate

Type Code

3,044

Publication Type

Journal

Publication Title

Journal of Reproductive Medicine and Embryology

Publication Link

https://jrme.journals.ekb.eg/

MainTitle

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

Details

Type

Article

Created At

09 Apr 2025