CleverHealth Network projects facilitate diagnostic reliability and improve patient safety

Finland is a model country for data on health and well-being. Now the aim is to combine that data with the newest technological solutions to improve existing treatments. The CleverHealth Network ecosystem, founded in 2017, has already started four projects bringing medical professionals and the know-how from the corporate world together to change the way healthcare works.

In these CleverHealth Network ecosystem collaborative projects, professionals from HUS, top researchers from universities, and experts from businesses from different technological fields develop new solutions to well-defined clinical challenges. What that results in is not only better medical care for the Finnish people but also successful health technology service and product innovations to businesses.

Digital solutions for healthcare also play a significant role in the future of HUS.

"We want to make the customer interface as smooth as possible, and digitalisation is the solution to that. Digitalisation makes it also easier for doctors and nurses to have more time to interact with patients during care pathways due to a reduced workload", says CEO of HUS Juha Tuominen.

Artificial intelligence helps diagnose cerebral haemorrhage

Technological solutions make doctors’ work easier and can help with diagnosing. A model example of this is the collaborative project between HUS, CGI, and Planmeca that utilises artificial intelligence to interpret CT scan, or computed tomography scan, images of the head area and to identify subarachnoid haemorrhaging.

The project is going to help with a problem that plagues many hospital districts: while the number of different imaging tests taken is rapidly increasing, the amount of radiologists that interpret the results is decreasing. Mostly it is the doctor on call who needs to do the interpreting.

"The machine won't be making the diagnosis, but it can help the doctor spot any abnormalities in the images", clarifies HUS Project Manager Taru Hermens.

In the the project, bleeding and other abnormalities in head CT images showing  subarachnoid haemorrhaging have been segmented by hand. Then the neural network has been taught to identify bleeding. 

"We have really hit our stride in the past year, and the project has progressed well. Last year, the first algorithm capable of identifying a specific type of bleeding in a reliable way was created", says Hermens. 

The development of the algorithm is continuous. The next step is to help the neural network identify also other types of bleeding. 

Data can help improve patient safety

In some cases, technological solutions can have a direct impact to the lives of patients, such as by making the everyday life of diabetes patients easier. The aim of the CleverHealth Network's ‘Child with diabetes’ project is to increase patient safety and the safety of data communication using a common European platform model.

The lives of diabetes patients have already been made easier through the development of different subcutaneous continuous glucose monitoring sensors and insulin pumps that require no separate insulin injections.

"These means help gather important data on the patients, and the project has made it easier for their doctors to have access to it. A digital consent solution based on open source code has been developed in the project for parents to be able to authorise the hospital to be given access to the data gathered at home upon the doctor's request", says Project Manager Birgit Paajanen from HUS.

The aim is to enable the expansion of safe data communication from e.g. diabetes care sensors and pumps to the health care personnel with the parents’ approval. The parents will, in turn, be able to see who has used the data and for what purpose. Once it has been verified the new open source code works, it will be used also in other diagnostic groups and to bring consent-based data also to the CE-marked HUS data lake in accordance with the new EU General Data Protection Regulation (GDPR).

"In the first phase of the project, we have now built this scalable, transparent, and consent-based data communication structure, through which data can be transferred to the use of health care professionals", Paajanen says.

The project is a collaboration with Sitra's IHAN project. The IHAN project aims to build the foundation for a fair data economy, and the participants include Finland and several other European countries, as well as e.g. the global MyData network. The open source code created in the project will also be published on the Github platform, making it available for the use of the whole developing network. The code will not include any HUS-specific data.

The results and aims of the ‘Child with diabetes’ project have also been published in the European EHTEL (the European Health Telematics Association) symposium in Barcelona in December 2019.

More information

  • Head area imaging analytics
    Taru Hermens, Project Manager, taru.hermens[at]
    Miikka Korja, Chief Innovation Officer, Head of Section - Cerebrovascular Consultant, Associate Professor of Neurosurgery, miikka.korja[at]
  • Child with diabetes / IHAN (Sitra)
    Birgit Paajanen, Project Manager, birgit.paajanen[at]
    Päivi Miettinen, Chief Physician, HUS Children and Adolescent, paediatric endocrine clinic, paivi.miettinen[at]