Automated Decision Support and Guideline Verification in Clinical Practice

Applying international guidelines in medical, including cardiological, therapies is a guarantee of safe and modern treatment. Unfortunately, standards are often not obeyed. In this paper we present an experimental software program based on rough sets methods. The main aim of this application is to improve patient care and help the decision process using guidelines verification. We concentrate on the practical aspects using these methods. Examples and clinical tests, which were based on real-life data of our patients, show that the accuracy of results reached on a large group of patients could be acceptable in clinical practice. 1

Medical diagnosis support by the application of associational cognitive maps

The objective of the presented research is to construct a model of a patient's health that is based on the idea of cognitive map, a graphical knowledge-representation tool. The application of the proposed model for medical diagnosis is the practical goal of the research. Initially, we provide a brief review of the related works on medical decision support systems and cognitive maps. Afterwards, we sketch the general idea of the conceptual approach to the representation of medical knowledge and provide a new formulation of the medical diagnosis problem. Then, we define our model based on associational cognitive maps and show how it can be applied to diagnosis support. Due to the relative ease of understanding of cognitive map, the model can be easily interpreted and used, thereby making medical knowledge widely available through computer consultation systems. The application example presented is based on a relatively simple, real medical case