AI application for treatment of gestational diabetes
The number of women with gestational diabetes has increased substantially within the last 10 years both in Finland and globally. CleverHealth Network is launching a development project to support the treatment of gestational diabetes with a new digital service model based on artificial intelligence.
The project aims to improve the treatment and monitoring of gestational diabetes by developing a mobile application for measuring the mother’s glucose levels, physical activity, nutrition, pulse and daily weight and storing it in the cloud in real time.
“By improving lifestyle during pregnancy, we can probably reduce the number of mothers who will develop type 2 diabetes as well as the health risks to the child, thereby also improving the health of future generations. The application will help the patient to learn how her diet, activity and sleep affect blood glucose levels and weight gain and, consequently, the course of the pregnancy and the newborn’s health,” says Saila Koivusalo, research director of the project and specialist in obstetrics and gynaecology.
The application will forward the data in real time to health care personnel, who can provide guidance and support as needed. This means that the application is integrated into the care pathway instead of being a separate element, which is its greatest benefit compared to other health applications.
“With this service, we can offer even better, modern treatment. The service will also increase the efficiency of the treatment process for women with gestational diabetes, as the number of appointments requiring a hospital visit is expected to decrease,” Koivusalo says.
The project will make use of machine learning to provide guidance and treatment that are in line with the patient’s risk profile and meet her individual needs. Artificial intelligence also makes it possible to draw up predictions of both the mother’s and the child’s future health.
“This means, for example, that we can predict future glucose levels and propably also the newborn’s weight and adiposity in an unprecedented way. The application uses these predictions to give feedback automatically and advise the mother in making compensatory choices,” Koivusalo explains.
Project participants
More information
Mikko Kytö, Development Manager, mikko.kyto[at]hus.fi
Saila Koivusalo, Specialist in Obstetrics and Gynecology, M.D., PhD, Adjunct Professor, Development Manager, saila.koivusalo[at]hus.fi
