Research project EXTREMUM
The goal of thid cross-disciplinary collaboration is to design and implement a novel data management and analytics framework for medical data sources. The focus is on explainable machine learning methods as well as on legal and ethical aspects of the predictive models.
The EXTREMUM (Explainable and Ethical Machine Learning for Knowledge Discovery from Medical Data Sources) project can in simple terms be described as a machine learning initiative whereby useful knowledge is extracted from databases comprising medical data. The knowledge that is sought relates to the adverse effect of certain prescription drugs in order that adverse effects can be predicted and prevented. The same applies to the detection and predictive treatment of patients in relation to cardiovascular diseases. The ultimate goal of the project is to develop a prototype system that can be used to achieve the above insights from health data
Project members
Project managers
Panagiotis Papapetrou
Professor, deputy head of department
Members
Stanley Joel Greenstein
Universitetslektor, docent
Lars Asker
Senior lecturer
More about this project
