Glaucoma is a progressive disease of the optic nerve that causes damage to the optic nerve head and nerve fibre layer. Artificial intelligence models are currently being developed for early detection of glaucoma.
Researcher and project manager Ara Taalas specialises in data science, artificial intelligence and machine learning algorithms in medicine. One of his research objectives, in a joint project involving the Institute for Molecular Medicine Finland (FIMM) and Terveystalo health clinic, is to develop effective learning algorithms for glaucoma detection. Previously, Taalas modelled stem cell differentiation processes and worked in drug design.
When developing the artificial intelligence model, Ara Taalas focused on how the nerve layers of the fundus appear in the photographs. The algorithm will help to detect changes in the fundus pictures that can indicate damage to the nerve fibre layer.
Taalas uses the computing services of Finland’s ELIXIR node CSC. He develops models together with researchers in FIMM’s Machine Learning in Biomedicine team, and the same source code can be used on the computing servers of both CSC and Terveystalo.
“Finland is at a high level in terms of data management, but individual healthcare actors typically do not have a comprehensive picture of their patients – patient data is often scattered between various service providers. When customers go to a different organisation, the data does not follow them, which may make diagnosis and treatment more difficult. From the viewpoint of a researcher, the ideal thing would be to have a site for the entire country where each patient’s medical history could be found in its entirety.”
Data description should also be standardised.
“The structure of patient data systems has a major effect on the usability of any data entered into it. Fields where data can be entered in free form may be convenient for the person typing it in, but cause a lot of trouble to data analysts when trying to utilise it. Analysts often have to do a lot of work to standardise the data and to identify entries that contain errors. Modern patient data systems have in this respect become better in that they are much more structured.”
Read more here
CSC – IT Center for Science
is a non-profit, state-owned company administered by the Ministry of Education and Culture. CSC maintains and develops the state-owned, centra- lised IT infrastructure.
https://research.csc.fi/cloud-computing
ELIXIR
builds infrastructure in support of the biological sector. It brings together the leading organisations of 21 Euro- pean countries and the EMBL European Molecular Bio- logy Laboratory to form a common infrastructure for biological information. CSC – IT Center for Science is the Finnish centre within this infrastructure.
ELIXIR is partly funded by the European Commission