Remote monitoring of chronical pathologies using personalized Markov models

Laurent Jeanpierre 1 François Charpillet 1
1 MAIA - Autonomous intelligent machine
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : In this paper, an efficient method for diagnosing medical pathologies is presented, which is particularly adapted to long term monitoring of patients. It results from the collaboration between the LORIA (Lorrain Research Laboratory of Computer Science and its Applications), and the ALTIR (Lorrain Association for Renal Failure Treatments). An important aspect of our approach is that the physician can customize each patient's model. This model is expressed in medical terms, simplifying the interaction of physicians with the intelligent system. The approach will be illustrated with the remote monitoring of patients suffering from kidney disease. In a two years prospective randomized study, 15 patients have been monitored by our system, while 15 others were monitored the classical way. The two groups' statistics has shown that the system was really beneficent to patients' health. This experiment has led to the creation of the DIATELIC enterprise, to promote and develop this system.
Type de document :
Communication dans un congrès
First International Conference on Computational Intelligence in Medicine and Healthcare 2003 - CIMED 2003, 2003, Sheffield, Angleterre, 6 p, 2003
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https://hal.inria.fr/inria-00099567
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Soumis le : mardi 26 septembre 2006 - 09:38:45
Dernière modification le : jeudi 11 janvier 2018 - 06:19:51

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  • HAL Id : inria-00099567, version 1

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Laurent Jeanpierre, François Charpillet. Remote monitoring of chronical pathologies using personalized Markov models. First International Conference on Computational Intelligence in Medicine and Healthcare 2003 - CIMED 2003, 2003, Sheffield, Angleterre, 6 p, 2003. 〈inria-00099567〉

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