Biomedical subjects

L Portinale

Publications and source records attributed to L Portinale.

4 recordsLinked to original sources

PubMed2001

Cased-Based Reasoning for medical knowledge-based systems.

In this paper we present the results of the MIE/GMDS-2000 Workshop 'Case-Based Reasoning for Medical Knowledge-based Systems'. While in many domains Cased-Based Reasoning (CBR) has become a successful technique for knowledge-based systems, in the medical field attempts to apply the complete CBR cycle are rather exceptional. Some systems have recently been developed, which on the one hand use only parts of the CBR method, mainly the retrieval, and on the other hand enrich the method by a generalisation step to fill the knowledge gap between the specificity of single cases and general rules. And some systems rely on integrating CBR and other problem solving methodologies. In this paper we discuss the appropriateness of CBR for medical knowledge-based systems, point out problems, limitations and possible ways to cope with them.

Artificial Intelligence↗

PubMed2000

Diabetic patients management exploiting case-based reasoning techniques.

In this paper we propose a case-based decision support tool, designed to help physicians in 1st type diabetes therapy revision through the intelligent retrieval of data related to past situations (or 'cases') similar to the current one. A case is defined as a set of variable values (or features) collected during a visit. We defined taxonomy of prototypical patients' conditions, or classes, to which each case should belong. For each input case, the system allows the physician to find similar past cases, both from the same patient and from different ones. We have implemented a two-steps procedure; (1) it finds the classes to which the input case could belong; (2) it lists the most similar cases from these classes, through a nearest neighbor technique, and provides some statistics useful for decision taking. The performance of the system has been tested on a data-base of 147 real cases, collected at the Policlinico S. Matteo Hospital of Pavia. The tool is fully integrated in the web-based architecture of the EU funded Telematic management of Insulin Dependent Diabetes Mellitus (T-IDDM) project.

Case-Control Studies↗

PubMed2000

A multi-modal reasoning methodology for managing IDDM patients.

We present a knowledge management and decision support methodology for insulin dependent diabetes mellitus (IDDM) patients care. Such methodology exploits the integration of case based reasoning (CBR) and rule based reasoning (RBR), with the aim of helping physicians during therapy planning, by overcoming the intrinsic limitations shown by the independent application of the two reasoning paradigms. RBR provides suggestions on the basis of a situation detection mechanism that relies on formalized prior knowledge; CBR is used to specialize and dynamically adapt the rules on the basis of the patient's characteristics and of the accumulated experience. When the case library is not representative of the overall population, only RBR is applied to define a therapy for the input situation, which can then be retained, enriching the case library competence. The paper reports the first evaluation results, obtained both on simulated examples and on real patients. This work was developed within the EU funded telematic management of insulin dependent diabetes mellitus (T-IDDM) project, and is fully integrated in its web-based architecture.

Bayes Theorem↗

PubMed1999

Supporting decisions in diabetic patients management through case-based retrieval.

In this paper we present a tool for the intelligent retrieval of past cases to support Insulin Dependent Diabetes Mellitus patients therapy revision. This tool was designed for assisting physicians during periodical monitoring visits. Each case is represented through i) a collection of features that describe the patient's clinical state at the decision time, i.e. the control visit, ii) the decision taken in terms of therapy revision and iii) the outcome obtained on the metabolic control during the following monitoring period. A new case is first classified into a protypical monitoring situation, and then similar cases are retrieved and shown to the user. This tool is fully integrated in a Web-based distributed system for Diabetes Management, developed within in the EU project T-IDDM.

Decision Support Techniques↗