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Announced in August 2020, MOGGE foundation artificial intelligence (AI) unit represents one of earliest, if not the first, AI unit that is committed to medical field in the Middle-East. 


The message of this unit is to enhance the culture of AI in medicine in the Middle-East and to develop efficient approaches to improve medical care and support individualized medicine.


This unit works in proximal collaboration with MOGGE research committee, namely beta team which is responsible for conduction of multicenter studies, which design and collect large databases, which are suitable for machine learning models. The unit works in distal collaboration with MOGGE foundation software team (MoggeSoft), which is responsible for final development of clinical applications based on results from machine learning algorithms. 

Achievements and ongoing work

  • Shazly S, Hortu I, Shih JC, Melekoglu R, Fan S, Karaman E, Fatkullin I, Pinto P, Irianti S, Tochie J, Abdelbadie A. Prediction of Clinical Outcomes in Women with Placenta Accreta Spectrum Using Machine Learning Models: An International Multicenter Study 

  • MOGGE PAR-A and PAR-P scores: a software driven from a machine learning model that predicts clinical outcomes of PAS


Ongoing projects

  • Endometrial cancer prognosis (ECID project)

  • Abnormal uterine bleeding - Individualized management


SilverAxon inc. is the software extension of AI unit, which serves to produce the final software products that convert AI-created models to easy-to-use clinical tools. 

SilverAxon first product is MOGGE PAR-A calculator, which emerged from our original study.

Currently, SilverAxon is working with AI unit on the current project (ECID) which aims at serving endometrial cancer patients

Are you a MOGGE AI unit member?

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MAY 2021

MOGGE foundation sponsors a new initiative that comprises creation of an international network of investigators and departments that supports expansion of clinical research and applications of artificial intelligence in the field of obstetrics and gynecology