Medical expert systems

Description of the product

Modern medicine offers very diverse treatment approaches, which are rapidly evolving through intensive research. As a result, it is becoming increasingly difficult for healthcare professionals to stay up-to-date and find the best solution from many options for each patient. A medical expert system, like a human expert, helps to find solutions to medical problems.


Keystone of an expert systems is a knowledge base that represents expert knowledge, such as how to treat a disease. Since this knowledge is often only available in the form of publications or as results of clinical studies, it must be consolidated and converted into a formal knowledge model. During the use of the expert system, this model is then applied to input values, e.g. current blood levels. As a result, the expert system can offer information visualizations up to concrete recommendations for actions.

In the project OnkoLeit a software product of the same name is developed, which supports the treating physician with respect to diagnosis and therapy decisions for oncological diseases.


Interactive Analysis and Diagnosis department

Would you like to learn more about our competence and service spectrum in the field of Interactive Analysis and Diagnosis? Then visit the IAD department page.


Other projects of the IAD department

Here you can find more projects with participation of the Interactive Analysis and Diagnosis department.



OnkoLeit supports the treating physician in diagnosis and therapy decisions in the case of oncological diseases.



Philipp, Patrick; Beyerer, Jürgen; Fischer, Yvonne:
Expert-based probabilistic modeling of workflows in context of surgical interventions. In: Schaefer, K.; Institute of Electrical and Electronics Engineers; IEEE Communications Society; IEEE Systems, Man, and Cybernetics Society: IEEE Conference on Cognitive and Computational Aspects of Situation Management, CogSIMA 2017: March 27-31, 2017, Savannah, GA, USA. Piscataway, NJ: IEEE, 2017, S.77-83. 


Philipp, Patrick; Bleier, Johannes; Fischer, Yvonne; Beyerer, Jürgen:
Towards a surgical phase detection using Markov Logic Networks. In: Radermacher, Klaus (Ed.); Society for Computer Assisted Orthopaedic Surgery, Bern: CAOS 2017, 17th Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery. Papers. Online resource: June 14-17, 2017, Aachen, Germany, S.288-294. (EPiC Series in Health Sciences 1)


Philipp, Patrick; Fischer, Yvonne; Hempel, Dirk; Beyerer, Jürgen:
Framework for an interactive assistance in diagnostic processes based on the translation of UML activities into petri nets. In: Arabnia, Hamid R. (Ed.); Institute of Electrical and Electronics Engineers; American Council on Science and Education, Las Vegas/Nev.: International Conference on Computational Science and Computational Intelligence, CSCI 2015. Proceedings: 7-9 December 2015, Las Vegas, Nevada, USA. Los Alamitos, Calif.: IEEE Computer Society Conference Publishing Services (CPS), 2015, S.732-737.