Cooperative Medical Diagnoses Elaboration by Physicians and Artificial Agents

Cooperative medical diagnosis systems seem to be well suited for the solving of many difficult medical diagnosis problems, like the combinations of illnesses where between the illnesses treatments are dependencies. The solving of many difficult medical problems requires knowledge from different medical domains, which cannot be detained by a single physician or a medical computational system. In this paper, a novel medical multiagent system called MASM (Medical Assistant Multiagent System) that can help physicians in their work is proposed. Are analyzed advantages of the cooperative problems solving by physicians and the proposed multiagent system. By cooperation, the human and artificial thinking advantages in the diagnostics elaboration are combined. The proposed multiagent system is a complex system. It is composed from relatively simple agents, which can discover cooperatively emergent properties that arise during the medical problems solving processes that can be ignored by the physicians. Discovered informations allows to the MASM system to increase the accuracy of the elaborated diagnostics and reduce the complexity of the diagnosis processes.