AUTHOR=Popova Polina , Anopova Anna , Vasukova Elena , Isakov Artem , Eriskovskaya Angelina , Degilevich Andrey , Pustozerov Evgenii , Tkachuk Alexandra , Pashkova Kristina , Krasnova Natalia , Kokina Maria , Nemykina Irina , Pervunina Tatiana , Li Olga , Grineva Elena , Shlyakhto Evgeny 

TITLE=Trial protocol for the study of recommendation system DiaCompanion with personalized dietary recommendations for women with gestational diabetes mellitus (DiaCompanion I)

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2023.1168688

DOI=10.3389/fendo.2023.1168688

ISSN=1664-2392

ABSTRACT=Gestational diabetes mellitus (GDM) is a common complication of pregnancy associated with serious adverse outcomes for mothers and their offspring. Achieving glycaemic targets is the mainstream in the treatment of GDM in order to improve pregnancy outcomes. As GDM is usually diagnosed in the third trimester of pregnancy, the time frame for the intervention is very narrow. Women need to get new knowledge and change their diet very quickly. Usually, these patients require additional frequent visits to healthcare professionals. Recommender systems based on artificial intelligence could partially substitute healthcare professionals in the process of educating and controlling women with GDM, thus reducing the burden on the women and healthcare systems. We have developed a mobile-based personalized recommendation system DiaCompanion with data-driven real time personal recommendations focused primarily on postprandial glycaemic response prediction. The study aims to clarify the effect of using DiaCompanion on glycaemic levels and pregnancy outcomes in women with GDM.