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Objective is to create an assessment, based on health data, of each person’s risk of cardiovascular diseases

Cardiovascular diseases are the most common cause of death in the world. Andrea Ganna, Group Leader from Institute for Molecular Medicine Finland FIMM at the University of Helsinki and instructor from Harvard Medical School, wants to establish a nationwide, personalised risk assessment as foundation for planning public health interventions. The assessment is based on the health, demographic and genetic information of the citizens.

Andrea Ganna and his group is developing artificial intelligence (AI) approaches to model health trajectories. According to Ganna, cardiovascular diseases are ideally suited for analysis by artificial intelligence, since their treatment is preventive. ”Accurate identification of individuals at high risk is one of the cornerstones of primary prevention of cardiometabolic diseases,” he says. The study is based on combining genome information with digital health care data from national health registries. “We are talking about huge data sets. Every year there are millions and millions of new medication purchases and diagnoses. To scale and to leverage this massive data, deep learning methods are needed.”

Deep learning methods need large supercomputing infrastructure. “CSC has created a secure environment for this computation. Without a secure supercomputing environment, we could not carry out this project. To be successful, we need, on the one hand, research and development, and, on the other hand, a powerful computing environment.”

Patient data is important for research, but personal data is also protected. “We need to guarantee individuals’ privacy but, at the same time, we need to integrate a lot of personal data to really leverage the power of artificial intelligence/deep learning approaches to better target public health interventions. Generating synthetic health trajectories will help to respect privacy and, at the same time, to combine a lot of personal information within Finland, but also across Nordic countries.”

”My hope is that personal data that is routinely collected in healthcare can help and benefit everyone. My hope is that that this information can help doctors to make better decisions, but also help patients in motivating life style changes. Thus everyone is helping everyone.”

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