Achrafieh, Beirut , Lebanon


Middle East Fertility Society



Developed in Cooperation with

Middle East Fertility Society (MEFS)  Symposium at AASRM 2022

Monday, October 24, 2022

 1:30 PM - 2:45 PM


Target Audience

This advanced level inter-professional course is designed for physicians, advanced practice providers, nurses, ART allied health professionals, practice managers, embryologists, and scientists.

Credit Type

Needs Assessment

ART future may soon depend on the integration of non-invasive new-generation technologies into novel computational analyses to generate more accurate prediction models for embryo implantation. The potential for Artificial Intelligence (AI) and Machine Learning (ML) to usher in a new era of standardization, automatization, and precision in reproductive medicine has generated lots of enthusiasm. Many reproductive physicians and biologists stand overwhelmed by a rapidly evolving technology which is felt by many to have taken our field by surprise as more publications are emerging every day. An overview of existing AI and ML technologies in reproductive medicine is therefore very timely.


This symposium appraises the current and emerging applications of artificial intelligence and machine learning in the field of Reproductive Medicine. It sheds the light on AI-based predictive models under development to improve ART cycle management and outcomes. It also emphases the potential role for machine learning in the selection of gametes and embryos during the IVF/ICSI process. While it describes the future potential of the new technology in our field, it also acknowledges its limitations and challenges.

Learning Objectives

At the conclusion of this session, participants should be able to:

  1. Identify the potential role for AI-based predictive models in improving patient selection, treatment protocols and cycle outcomes.
  2. Explain the relevance of machine learning in gamete/embryo selection and prediction of successful implantation.
  3. Categorize the potential benefits, challenges and limitations of machine learning and artificial intelligence applications in reproductive medicine.


      • Weill Cornell Medicine
      • ART Compass App
      • Cairo University , Egyptian IVF center


      • Sidra Medical & Research Center


ACGME Competencies



PG 20

Strategies to Improve the Safety of Controlled Ovarian Stimulation Protocols: CME
Paving the Way for Ohss-Free IVF?