For the Austrian National Member Organization, ASA studied the field of medicine, where big data analysis is already shaping the understanding of diseases.
A unique dataset of all Austrian patients under medical treatment for diabetes was compiled in 2006-2007 comprising detailed data on 325,000 patients. Using this large database, scientists revealed a significant extra risk of developing diabetes triggered by undernourishment in early life . Other scientists identified diabetic co-morbidities, both well-known (such as retinopathies, hypertension, chronic kidney diseases etc.)   and some not known earlier (such as epilepsy, sepsis, mental disorders).
In 2013 ASA began to develop tools that will allow added value to be gained from large data collections.
 Thurner S, Klimek P, Szell M, Duftschmid G, Endel G, Kautzky-Willer A, Kasper DC (2013). Quantification of excess-risk for diabetes when born in times of hunger, in an entire population of a nation, across a century. Proceedings of the National Academy of Sciences USA, 110 (12), 4703—4707.
 Klimek P, Kautzky-Willer A, Chmiel A, .Schiller-Frühwirth I, Thurner S (under review). Quantifying age- and gender-related diabetes comorbidity risks using nation-wide big claims data.
 Thurner S, Klimek P, Szell M, .Duftschmid G, Ende G, .Kautzky-Willer A, Kasper DC (2013). Reply to Klitz and Niklasson: Can viral infections explain the cross-sectional Austrian diabetes data? Proceedings of the National Academy of Sciences USA, 110 (30), E2751.
The work on Austrian diabetes data is of relevance to IIASA's Austrian National Member Organization.
ASA’s main collaborators in the field of Big data analysis include D. Farmer, Professor, Oxford University, UK; C. Mascolo, Professor, Cambridge University, UK; F. Taddei, Professor, CRI Paris VI, France.
Last edited: 21 May 2014
International Institute for Applied Systems Analysis (IIASA)
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