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Different approaches applied to the contextual medical decision problem

Kurzyński M., Puchała E., Woźniak M.

Journal of Medical Informatics & Technologies

2001

Vol. 2, Part. 1

MI147--MI153

In many diagnostic problems there exist dependencies between successive states object and applied control. This situation is typical for the medical decision task, i.e. the recognition of the human acid-base state. We will present neural networks, probabilistic and fuzzy approach applied to the medical decision problem with context.

The project of expert system aided decision process in medicine

Puchała E.

Journal of Medical Informatics & Technologies

2000

Vol. 1

CS 65--70

The paper deals with a concept of the expert system for family doctor practices. This system will be realized by Division of Systems and Computer Networks Wroclaw University of Technology in co-operation with Medical Academy of Wroclaw. The family doctor loads data (by user interface) to the system, which describes patients state of health. By this way we can obtain, so-called feature vector. Data in feature vector, may be complete by information collecting from different type of diagnosis equipment like electrocardiograph, Rontgen unit, ultrasonic unit and so on. Number of features may be optional, but for investigation goals only 25 features were used. The user can load to the system less then 25 features. It is important in case then we have problems with results of medical examination extraction. On the basis of a patient information, system gives us decisions which aided medical treatment. Information from data base (set of feature vectors) is processed by expert system. It leads to so called “statistical data base” establishment. System consists of three functionally connected parts: 1. data collecting and data processing, 2. decision part, 3. user’s interface. Expert system can give us unlimited number of decision. In the decision expert system, adaptive algorithms are used. It means that in case of some features are not available, expert system starts algorithms which these feature estimates (algorithms take into account whole patients population’s features and typical for individual patient features).

Celem pracy jest przedstawienie opracowywanego w Zakładzie Systemów i Sieci Komputerowych Politechniki Wrocławskiej projektu systemu ekspertowego wspomagającego podejmowanie decyzji lekarskich. W założeniu, system funkcjonuje w oparciu o „statystyczną” bazę wiedzy współpracującą z oryginalnymi algorytmami wnioskowania.