DADEL

Project leader:

• Lars Asker, Associate Professor, DSV, SU

Researchers

• Isak Samsten, Postdoctoral Researcher, DSV, SU
• Panagiotis Papapetrou, Professor, DSV, SU

Partners

• Stockholm County Council

Project period: 2012-01-01 to 2016-12-31

Funding: Stockholm County Council and Stockholm University

Budget: 19M SEK

Description

In Swedish: Dataanalys för detektion av läkemedelseffekter (DADEL)

The main goal of the project is to develop techniques and tools to support decision making and discovery of drug effects by analyzing patient records, drug registries, case safety reports and chemical compound data in the form of both structured and unstructured (free text) data.

The project will contribute with novel approaches to data mining and clinical text mining and develop a platform for large-scale analysis of massive, heterogeneous and continuously growing data sets.

People

Lars Asker, Associate Professor

representation learning, healthcare applications

Isak Samsten, Senior Lecturer

explainability, temporal data mining, fintech

Panagiotis Papapetrou, Professor

sequential and temporal data mining, explainability, healthcare applications

Henrik Boström

Professor, KTH

Tuwe Löfström

Ph.D. (2015)- Now at Jönköping Univ.

Jing Zhao

Ph.D. (2017)- Now at EasyPark Group