Artificial intelligence prevents diseases and promotes wellbeing

Published in AI Finland blog on October 15, 2018

Self-reliant health maintenance and the risk mapping of diseases through various digital channels are new, important services for the future. These services, known as knowledge-intensive services, will be the foundation of our competitiveness. They are supported by the use of artificial intelligence in research and in the development of new products and services.

Artificial intelligence helps prevent diseases

The key to developing knowledge-intensive services is to be able to utilise the capabilities of data analytics and artificial intelligence to identify and diagnose, in particular, early-stage health risks. In the treatment of diseases, there is potential mainly in the automation of processes and the optimisation of work routines.

In the future, a machine-learning algorithm will be able to predict eventual health risks and support health promotion. An electronic check-up could analyse the current health status and utilise artificial intelligence and a chat interview to guide the person to an appropriate service.

Essential to manage and combine data

The above examples require specific capabilities to manage and utilise various data sources. Identification of disease risks and early diagnosis are increasingly dependent on combining various data sources and on the development of predictive algorithms.

Combining health records from patient registers, population research, genetic factors or lifestyle information is needed to get the most out of AI technology and machine learning. Finland has good patient registers and population-level health information registers, which enable the creation of new digital service paths, diagnostic tools and new business in the health sector.

Dialogue between professions important

The challenge is that various professions engage in only little dialogue on AI development. Combining medical research and AI research is still fairly new in Finland.

To be able to teach the machine to analyse medical imaging results, we must ensure access to extensive medical imaging archives and registers, and combine medical expertise with the development of machine learning. In addition, obtaining appropriate and high-quality data and combining it from various sources is still a major challenge.

Finland to become an international leader

The latest research data for both advanced analytics and ICT skills must be made available for utilisation. Creating artificial intelligence capabilities in the health sector requires expertise in the special features of the field, as well as understanding of the utilisation of artificial intelligence and machine learning. Raising this know-how is a good base for us on which to build a strong national knowledge network for research and innovation.

Its main task is to make Finland into an international leader in digital health research and innovation. Without a national knowledge network model, we won’t be competitive in the utilisation of artificial intelligence and machine learning in the health sector.

Text: Professor of Practice, Director Maritta Perälä-Heape
Centre for Health and Technology, University of Oulu

Last updated: 19.10.2018