Magdalena Szymkowiak

How to Acquire and Structuralize Knowledge for Medical Rule-Based Systems?

The intention of a medical expert system is to help doctors make right diagnostic and therapeutic decisions concerning, sometimes not very well-known to them, diseases. This expert system needs a high quality knowledge base. In order to design such a base one has to reach sources containing knowledge that is current, rich and based on reliable medical experiments. At the same time, due to various formats of this knowledge storing, its acquisition and structuralization to the form required by expert systems is not an easy task. Focusing our attention on medical rule-based systems, we propose the algorithms and tools that will be useful while designing such a knowledge base.

Characterizations of distributions through selected functions of reliability theory

ABSTRACT In this article, exponential distribution, two-parameter Weibull distribution, log-logistic distribution, log-log-logistic distribution, and Lomax distribution are characterized through selected functions of reliability theory: failure rate, aging intensity function, and log-odds rate.

Discovering Medical Knowledge from Data in Patients' Files

An Individual Patients File (IPF) includes information about a patient and the course of his illness over many years. During this period, the doctor, taking permanent care of the patient, puts various data and observations into his IPF. In the paper we propose a kind of probabilistic and statistical analysis of the data stored in collections of IPFs. The collections can be made accessible by means of a medical Semantic Web. The proposed analysis requires the data to be expressed in the form of Bernoulli variables. As a result, it gives us medical hypotheses, with their premises-facts, conclusions and reliabilities. They can be presented in the form of production rules, used in medical Rule-Based Systems for automatic reasoning.

Characterizations of the exponential distribution by Pascal compound

Abstract Under the reliability conditions NBU/NWU or IFRA/DFRA, the exponential distribution is characterized by stochastic ordering properties and by increasing convex ordering properties which link the Pascal compound with record values, spacing between record values and record values with a random index.

Generalized aging intensity functions

Next, we introduce and study the family of G-generalized aging intensity functions of univariate absolutely continuous lifetime random variables (Sect. 7.1). They allow to analyze and measure the aging tendency from various points of view. Moreover, the recognition of the shape of a properly chosen G-generalized aging intensity estimate admits a simple identification of the data lifetime distribution.

Some results about bivariate discrete distributions through the vector of aging intensities

ABSTRACT In this paper bivariate vectors of discrete aging and alternative aging intensities are introduced. Using these vector-valued functions we present some results about bivariate discrete distributions.

Machine Ranking of 2-Uncertain Rules Acquired from Real Data

There are many places (e.g. hospital emergency rooms) where reliable diagnostic systems might support people in their work. They could have form of RBSs with uncertainty and use the techniques of forward and backward chaining in their reasoning. The number and the contents of derived hypotheses depend then both on the form of the system’s knowledge base and on the inference engine performance. The paper provides detailed considerations on designing and applying particular uncertain rules, namely 2-uncertain rules. They are equipped with two reliability factors, representing a kind of second order probability. The rules can be acquired from real data of attributive representation. In the paper we propose a method for calculating the two reliability factors. We also suggest how to take advantage of the factors during reasoning, in order to obtain reliable hypotheses. The factors help to rank the rules and to fire them in the best order.

Cost-Effectiveness Analysis of Transferring Medical Data over P2P Network

In the paper, a transfer of medical dataover P2P network is considered. The data are homogenous, of textual type. They are transferred between the nodes representing medical systems, along transmission lines. Although only some of the nodes can produce, process or integrate data, all of the nodes are able to propagate them to their neighbours. The costs of building the transmission lines are high, so an optimum network topology is being searched. The random graphs with bounded degree are used for modelling of such networks. The process of transferring data over network is examined by means of the original algorithm RST for searching rooted spanning trees.