Fujitsu Leverages Artificial Intelligence for Treatment of Diabetes during Pregnancy

Fujitsu is supporting a new initiative to leverage artificial intelligence to improve the detection and treatment of diabetes during pregnancy. The project aims to improve the treatment and monitoring of expectant mothers using a mobile application to track and measure key lifestyle factors and blood glucose data. Fujitsu is delivering data integration and modeling services in addition to creating a user interface to visualize patients’ data, enabling healthcare professionals to recommend personalized treatment.

Gestational diabetes occurs when the body cannot produce enough insulin – a hormone that helps control blood sugar levels – to meet the extra needs during pregnancy. It does not usually cause any symptoms but can lead to premature birth or difficulties during childbirth. The new project is undertaken via the Finnish CleverHealth Network and coordinated by HUS Helsinki University Hospital. It uses machine learning to analyze healthcare data and provide healthcare professionals with enhanced insights into the health of mothers-to-be who may be at increased risk of diabetes during pregnancy, as well as providing guidance and treatment tailored to individual needs and risk profiles.

According to HUS, of the 52,000 women who give birth in Finland every year, approximately 18 per cent – or nearly 10,000 – are diagnosed with gestational diabetes. Of these, roughly half develop type 2 diabetes at a later date, where the pancreas does not produce enough insulin or the body’s cells do not react to insulin. This amounts to 5,000 new diabetics per year, whose total treatment costs can accumulate to 28 million euros. The CleverHealth Network project aims to improve the treatment and monitoring of gestational diabetes. To do so, it is developing a mobile application for measuring and storing data relating to the mother’s blood glucose levels, physical activity, nutrition, pulse and daily weight – and making it available to healthcare professionals in real time.

Fujitsu is responsible for delivering data integration and modeling services to ensure that data is compatible with both HUS’s data lake and the Finnish National Personal Health Records (Kanta PHR). This is a national data repository where individuals are able to access and manage their own personal health records. Fujitsu is also designing a user interface that will enable health care professionals to easily interpret information.

Mikko Lampinen, Head of Public Sector and Healthcare Sales at Fujitsu Finland says: “This project involves bringing together multiple different technologies developed by Fujitsu in Japan and Finland to create a new service platform that leverages sensor data and analytics. As well as being able to extract insights, it is important to display data in a meaningful, clear way, providing actionable analytics for healthcare professionals to act upon. Consequently, we are designing an interface that clearly flags any anomalies in addition to showing all key data at a glance.”

The project is making use of machine learning to provide guidance and treatment tailored to each patient’s individual needs, based on her unique risk profile. The deployment of AI also makes it possible to predict both the mother’s and the child’s future health in a previously unprecedented way. For example, AI-powered insights can anticipate a mother’s future blood glucose levels in addition to her newborn baby’s birth weight and body mass index (BMI), making it possible to provide very targeted preventative advice in terms of lifestyle and food choices.

Aki Lindén, CEO of HUS says: “The unique data collected from HUS and by the Helsinki University Hospital maternity center – one of the largest in Europe – provides an excellent starting point for collaboration between multiple stakeholders. We have a remarkable opportunity to revisit how we go prevent and treat many medical conditions by integrating high-quality research into clinical practice to develop an entirely new service. The agility of the CleverHealth Network ecosystem has enabled us to progress rapidly so far, and we are now starting the development of new services for this first development project.”