Art der Arbeit:

• Masterarbeit Informatik
• Diplomarbeit Informatik

Status:

Themenangebot

Ansprechpartner:

• Prof. Dr. Rainer Unland

Kurzfassung

At the University Duisburg-Essen, a holonic medical diagnostic system based on multi-agents technology  and swarm intelligence is developed through the last years.
The system combines the advantages of the holonic paradigm, multi-agent technologies and swarm intelligence in building a highly adaptive, scalable, flexible, reliable and robust Internet-based medical diagnostic system.
The medical diagnostic system is compound of three type of agents: a mediator agent, many diagnosis specialist agents and disease representative agents.
The mediator agent represents the diagnostic system interface to the diagnosis requester and to the physician/specialist evaluator. Several diagnosis specialist agents are becoming part of the ad-hoc holonic structure in order to provide a suitable diagnostic. The disease representative agents are related to each defined disease that can be a diagnosis result. A disease representative agent determines if a set of symptoms matches its own symptom pattern. 
In diagnosis retrieval process, the agents follow a specific swarm intelligence method to build a holonic structure that provides one or more possible diagnostics. Each diagnostic returned by the system has a probability to match the true diagnostic that, in common way, is determined by the physician. The diagnosis specialist agent of a certain level is forwarding the symptoms description data as computer readable patient pattern to other diagnosis specialist agents of a lower level in order to receive from them later on a diagnostic that can satisfy the symptoms constraints. Any  diagnosis specialist agent encapsulates a learning/teaching component and a disease specific component that are determining the agent capability to adapt or to adopt a new disease as representative.
This thesis has to contribute to the diagnosis specialist agent development by introducing the design and implementation of a learning/teaching component and of a disease specific module required by such an agent.
The following milestones have to be reached by the thesis:
1. Realization of a Learning Component for acquiring of new disease data from another agent or from a special system;
2. Realization of a Teaching Component for publishing of description data for actual disease that the diagnosis specialist agent contains.
3. Implementation of a Disease Specific Component to operate with standard format of the disease data and with operations that the disease specialist agent can perform on that data; standardization of the disease data has to be handled;

For implementation, one of the most common object oriented programming languages,   Java and C++ have to be used.