Healthcare has many challenges in form of monitoring and predicting adverse events as healthcare associated infections or adverse drug events. When and how many have occurred, how can one predict them? This talk will describe the research carried out at the Clinical text mining group at DSV/Stockholm University and the future research that will be carried out. Topics are detection of symptoms, diseases, body parts and drugs from Swedish electronic patient records, including deciding on the certainty of a symptom or disease and detecting adverse (drug) events. Current and future research are detecting early symptoms of cancer and de-identification of electronic patient records for secondary use. An overview of other researchers and groups in Scandinavia and Europe will be presented.

Curriculum Vitae:

Hercules Dalianis, born 20 July 1959, Dalianis is a professor in Computer and Systems Sciences at Stockholm University. Dalianis graduated in 1984 at KTH in Electrotechnical Engineering, (Civilingenjör), and received his PhD/Teknologie doctor) at KTH 1996. Dalianis was post doc researcher at University of Southern California/ISI in Los Angeles 1997-98. Dalianis was also post doc researcher (forskarassistent) at NADA KTH 1999-2003, moreover Dalianis held a three year guest professorship at CST, University of Copenhagen during 2002-2005, founded by Norfa, the Nordic council. Dalianis founded Euroling AB in year 2000. Euroling AB develops and delivers the web and intranet search engine SiteSeeker to over 350 customers, mostly Swedish governmental organisations. Dalianis works in the interface between industry and university and with the aim to make research results useful for society. Dalianis has specialized in the area of human language technology, to make computer to understand and process human language text, but also to make a computer to produce text automatically. Currently Dalianis is working in the area of clinical text mining with the aim to improve healthcare in form of better electronic patient record systems, presentation of the patient records and extraction of valuable information both for clinical researchers but also for lay persons as for example patients.