The sixth HEXAnord meeting took place in Zakopane, Poland, with participants
from Finland, Sweden, Norway, Denmark, Lithuania, Estonia and France.
The three-day meeting included lectures and discussions on annotation, machine learning, medical terminology and natural language processing.

Our invited speaker Dr. Frédérique Segond, from Objet Direct, Grenoble, France presented the ALADIN project. The goal with the project was to develop a system to detect Hospital Acquired Infections, HAI, from analysis of patient records in French. The system was developed by characterizing risk factors associated with hospital acquired infections as they may appear in the hospital medical records.

All Phd-students presented their different groupwork from the HEXAnords PhD training course part II, among that a new idea of a time based summarisation engine for patient records.

There was also time for visiting the Tatra mountains. Some of us did it with skis, by horse or by foot.

(Participants from DSV-Stockholm University, were Hercules Dalianis, Martin Hassel, Aron Henriksson, Maria Skeppstedt, Sumithra Velupillai, Mia Kvist, Hideyuki Tanushi and Sara Brissman.)

The HEXAnord group

Hideyuki

Happy skiers!

Our invited speaker Dr. Frédérique Segond

Kirsi and Sanna enjoying the sun

Our horse

I visited associate professor Wendy Chapman and her research group at iDash at the Division for Biomedical Informatics, UC San Diego, Supercomputing Center in La Jolla, as part of the Interlock collaboration. We discussed the possibility of sharing and releasing clinical textual data for research. One concrete problem discussed with  Dr. Lucila Ohno-Machado (Founding Chief) is that the physical storage of data outside of a country boarders might not be acceptable for each countries’ Ethical committee. One solution to this could be to store the data in each country and then share the data.  Next stop was at ISI/University of Southern California in Marina Del Rey, Los Angeles. I presented some of the research carried out of by our research group IT for Health and specifically how one can use clinical text mining to construct tools that physicians, nurses, clinical researchers and hospital management can make use of to improve the health care processes.