Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.

To propose a functional in vitro fertilization (IVF) prediction model to assist clinicians in tailoring personalized treatment of subfertile couples and improve assisted reproduction outcome.Construction and evaluation of an enhanced web-based system with a novel Artificial Neural Network (ANN) architecture and conformed input and output parameters according to the clinical and bibliographical standards, driven by a complete data set and "trained" by a network expert in an IVF setting.The system is capable to act as a routine information technology platform for the IVF unit and is capable of recalling and evaluating a vast amount of information in a rapid and automated manner to provide an objective indication on the outcome of an artificial reproductive cycle.ANNs are an exceptional candidate in providing the fertility specialist with numerical estimates to promote personalization of healthcare and adaptation of the course of treatment according to the indications.


Journal article


In vivo (Athens, Greece)

Publication Date





507 - 512


Assisted Reproduction Unit, 3rd Department of Obstetrics and Gynecology, University of Athens, Attikon Hospital, Athens, Greece


Humans, Prognosis, Pregnancy Outcome, Fertilization in Vitro, Ovulation Induction, Pregnancy, Models, Biological, Artificial Intelligence, Internet, Female