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S Fiocchi

Publications and source records attributed to S Fiocchi.

8 recordsLinked to original sources
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↗
PubMed1999

Protocol-based reasoning in diabetic patient management.

We propose a system for teleconsultation in Insulin Dependent Diabetes Mellitus (IDDM) management, accessible through the use of the net. The system is able to collect monitoring data, to analyze them through a set of tools, and to suggest a therapy adjustment in order to tackle the identified metabolic problems and to fit the patient's needs. The therapy revision has been implemented through the Episodic Skeletal Planning Methodi, it generates an advice and employs it to modify the current therapeutic protocol, presenting to the physician a set of feasible solutions, among which she can choose the new one.

Adult↗
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↗
PubMed1998

A distributed system for diabetic patient management.

This paper describes a telemedicine system for diabetic patients management, presenting its architecture, the technical solutions adopted and the methodologies on which it is based. The system, designed to provide decision support in a distributed environment, is composed of two modules, a Patient Unit and a Medical Unit, connected by telecommunication services. We outline how the two modules can interact to perform an effective monitoring and a cooperative control of glucose metabolism. In particular, we detail the data analysis tasks performed by the two units and how the results are exploited to assist patients and physicians in revising and adjusting the therapeutic protocol. We will finally describe the current prototypical implementation of the system that uses HTTP as the communication protocol and HTML pages as the graphical user interface.

Diabetes Mellitus, Type 1↗
PubMed1996

Distributed intelligent data analysis in diabetic patient management.

This paper outlines the methodologies that can be used to perform an intelligent analysis of diabetic patients' data, realized in a distributed management context. We present a decision-support system architecture based on two modules, a Patient Unit and a Medical Unit, connected by telecommunication services. We stress the necessity to resort to temporal abstraction techniques, combined with time series analysis, in order to provide useful advice to patients; finally, we outline how data analysis and interpretation can be cooperatively performed by the two modules.

Computer Communication Networks↗
PubMedDate not supplied

Anticardiolipin antibodies in first-degree relatives of type 1, insulin-dependent, diabetic patients.

First-degree relatives (FDRs) of diabetic patients are at risk of IDDM, and frequently present several autoantibodies. We detected anticardiolipin antibodies (aCL) in 42 FDRs, aged 12.4 +/- 4.2 years and in 52 controls. aCL (IgG and IgM) were measured by ELISA and their results expressed in arbitrary units. All FDRs underwent islet cell antibodies (ICA) measurement, intravenous glucose tolerance test and HbA1c levels. HLA typing and HLA-DQ molecular analysis were performed in all FDRs. Positive levels of aCL-IgG were observed in 8/42 FDRs and no control subject (p = 0.04); aCL-IgM values were similar in FDRs and controls. No correlation was found between aCL levels and chronologic age or HbA1c levels. No association was observed between aCL frequency and immunologic (ICA), metabolic or genetic (HLA) parameters. No FDR showed any feature of antiphospholipid syndrome. aCL-IgG presence in FDRs is suggestive of a need to carry out a follow-up study to establish the significance of these antibodies.

Adolescent↗