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OBG-AI21 project 
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OBG-AI 21 global network aims at connecting OBGYN departments worldwide, to establish a network specialized in OBGYN-related artificial intelligence research and technology.

          AI technology has been increasingly used in medicine since it was first introduced to the field of radiology in the late 90s. Since then, AI has been invested in many fields of medical research and medical care. Two of the most popular uses of AI technology are prediction models (traditional machine learning) and radiological diagnosis (deep learning).

          Although AI has been applied to medicine for more than 2 decades, its implementation in the field of OBGYN has been significantly postponed till the last 3 years when it has been brought under spot. Machine learning was used to create prediction models for many crucial issues such as postpartum hemorrhage and VBAC success. The current decade is anticipated to reveal many similar projects as more research groups become aware of the high predictive accuracy of machine learning.

          MOGGE foundation AI unit was launched in 2020 to commence an active participation in the field of AI as for OBGYN-based topics. The unit was able to complete a multicenter international study in collaboration with 11centers from 9 countries and established 2 machine learning-based prediction models (under reviewing) and produced their associated PC applications. This year, the unit aims at establishing a new research line to conduct OBGYN radiology-related projects that can read X-rays, CT, and MRI and conclude findings. As its activity expands, AI unit has decided to launch the OBG-AI 21 initiative to create a large collaboration of centers that are interested to be a part of AI-related projects worldwide.



Ismet Hortu
Lecturer, department of obstetrics and gynecology
Ege University School of Medicine, Izmir, Turkey

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Ali El-saman 

Professor, department of obstetrics and gynecology

Assiut University, Egypt


Nashwa Eltaweel
Academic clinical trainee
University hospitals of Coventry and Warwickshire, UK


Dema Adwan
Professor, department of obstetrics and gynecology
Damascus university and ASPU university, Damascus, Syria


Pedro Viana Pinto

Specialist, department of obstetrics and gynecology

Da Universidade do Porto, Portugal

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Rauf Melekoglu

Associate Professor, MD, PhD student in Biotechnology

Inonu University School of Medicine Department of Obstetrics and Gynecology, Malatya, Turkey


Federico Ferrari 

Consultant, department of obstetrics and gynecology

Spedali Civili di Brescia, Brescia, Italy


Sara El-Dessouky

Associate professor

Prenatal diagnosis and fetal medicine department - National Research Center, Cairo, Egypt


Jin-Chung Shih

Associate Professor, Department of Obstetrics and Gynecology
National Taiwan University Hospital, Taipei, Taiwan

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