Abstract
We present a successful application of Artificial Intelligence
(AI) methodologies in the context of a telemedicine service
for diabetic patients management, developed within the EU-funded
T-IDDM project. The system architecture is distributed, and composed
by a Patient Unit and by a Medical Unit, connected through
a telecommunication link. Several AI methods have been exploited
to implement the T-IDDM functionality. The data base relies on an
explicit representation of the domain ontology. Temporal Abstractions
and other Intelligent Data Analysis techniques are used to analyse
the patient’s monitoring data; the Case Based Reasoning (CBR)
methodology is applied to perform the Knowledge Management task.
Finally, CBR is integrated with Rule Based Reasoning to provide
physicians with a multi-modal reasoning decision support tool. The
T-IDDM service is being tested through a small on field trial in Pavia;
the first results, though preliminary, seem to substantiate the hypothesis
that the use of an AI-based telemedicine system could present
an advantage in the management of type 1 diabetic patients, leading
to a more tight control of the patients’ metabolic situation, in a
cost-effective way.
Lingua originale | Inglese |
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Pagine | 716-720 |
Numero di pagine | 5 |
Stato di pubblicazione | Pubblicato - 1 gen 2000 |
Evento | PAIS 2000, Prestigious Applications of Intelligent Systems / European Conference on Artificial Intelligence (ECAI -PAIS) ??? - Berlin, Germany Durata: 1 gen 2000 → … |
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???event.eventtypes.event.conference??? | PAIS 2000, Prestigious Applications of Intelligent Systems / European Conference on Artificial Intelligence (ECAI -PAIS) ??? |
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Città | Berlin, Germany |
Periodo | 1/01/00 → … |
Keywords
- Knowledge Representation
- Medical Informatics