Models towards Risk Behavior Prediction and Analysis: A Netherlands Case study

Autor: Adekunle, Onaopepo, Riedl, Arno, Dumontier, Michel

In many countries financial service providers have to elicit their customers risk preferences, when offering products and services. For instance, in the Netherlands pension funds will be legally obliged to factor in their clients risk preferences whe

Externí odkaz: http://arxiv.org/abs/2311.04164

Applied Data Science in the Pension Industry: A Survey and Outlook

Autor: Adekunle, Onaopepo, Dumontier, Michel, Riedl, Arno

The pension industry, much like the rest of the financial industry, is increasingly adopting data science and artificial intelligence-based solutions. Applications range from leaner and faster operations (“doing the same thing better”) to complet

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=narcis______::f15375cbbc4226daed87d4eb2e75b98d
https://cris.maastrichtuniversity.nl/en/publications/d2211dbb-ee18-4997-9908-b41b9436f098

A Privacy-Preserving Infrastructure for Analyzing Personal Health Data in a Vertically Partitioned Scenario

Autor: Sun, Chang, Ippel, Lianne, van Soest, Johan, Wouters, Birgit, Malic, Alexander, Adekunle, Onaopepo, van den Berg, Bob, Mussmann, Ole, Koster, Annemarie, van der Kallen, Carla, van Oppen, Claudia, Townend, David, Dekker, Andre, Dumontier, Michel

Publikováno v: Studies in Health Technology and Informatics, 264, 373-377. IOS Press

It is widely anticipated that the use and analysis of health-related big data will enable further understanding and improvements in human health and wellbeing. Here, we propose an innovative infrastructure, which supports secure and privacy-preservin

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=narcis______::9d0ea2bcccf251a2aa1039903bb54cb8
https://cris.maastrichtuniversity.nl/en/publications/032a0623-3d81-441a-a7ac-c89def46e02d

A Privacy-Preserving Infrastructure for Analyzing Personal Health Data in a Vertically Partitioned Scenario.

Autor: Sun C; Institute of Data Science, Maastricht University, Maastricht, The Netherlands., Ippel L; Institute of Data Science, Maastricht University, Maastricht, The Netherlands., van Soest J; Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Developmental Biology, Maastricht University, Medical Centre+, Maastricht, The Netherlands., Wouters B; Institute of Data Science, Maastricht University, Maastricht, The Netherlands., Malic A; Institute of Data Science, Maastricht University, Maastricht, The Netherlands., Adekunle O; Institute of Data Science, Maastricht University, Maastricht, The Netherlands., van den Berg B; Statistics Netherlands (Centraal Bureau voor de Statistiek), Heerlen, The Netherlands., Mussmann O; Statistics Netherlands (Centraal Bureau voor de Statistiek), Heerlen, The Netherlands., Koster A; Department of Social Medicine, CAPHRI Care and Public Health Research Institute, Maastricht University, The Netherlands., van der Kallen C; Department of Internal Medicine, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands., van Oppen C; Institute of Data Science, Maastricht University, Maastricht, The Netherlands., Townend D; Department of Health, Ethics and Society, CAPHRI Research School, Maastricht University, Maastricht, The Netherlands., Dekker A; Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Developmental Biology, Maastricht University, Medical Centre+, Maastricht, The Netherlands., Dumontier M; Institute of Data Science, Maastricht University, Maastricht, The Netherlands.

Publikováno v: Studies in health technology and informatics [Stud Health Technol Inform] 2019 Aug 21; Vol. 264, pp. 373-377.