Combining conceptual graphs and argumentation for aiding in the teleexpertise.

Journal: Computers in biology and medicine
Published Date:

Abstract

Current medical information systems are too complex to be meaningfully exploited. Hence there is a need to develop new strategies for maximising the exploitation of medical data to the benefit of medical professionals. It is against this backdrop that we want to propose a tangible contribution by providing a tool which combines conceptual graphs and Dung׳s argumentation system in order to assist medical professionals in their decision making process. The proposed tool allows medical professionals to easily manipulate and visualise queries and answers for making decisions during the practice of teleexpertise. The knowledge modelling is made using an open application programming interface (API) called CoGui, which offers the means for building structured knowledge bases with the dedicated functionalities of graph-based reasoning via retrieved data from different institutions (hospitals, national security centre, and nursing homes). The tool that we have described in this study supports a formal traceable structure of the reasoning with acceptable arguments to elucidate some ethical problems that occur very often in the telemedicine domain.

Authors

  • Mamadou Bilo Doumbouya
    Université de Toulouse, Laboratoire de Génie de Production (LGP), EA 1905, 47 Avenue d׳Azereix, BP 1629, 65016 Tarbes Cedex, France; Université de Toulouse, Faculté de droit, 2 rue du Doyen Gabriel Marty, 31042 Toulouse cedex 9, France. Electronic address: mdoumbou@enit.fr.
  • Bernard Kamsu-Foguem
    Université de Toulouse, Laboratoire de Génie de Production (LGP), EA 1905, 47 Avenue d׳Azereix, BP 1629, 65016 Tarbes Cedex, France. Electronic address: bernard.kamsu-foguem@enit.fr.
  • Hugues Kenfack
    Université de Toulouse, Faculté de droit, 2 rue du Doyen Gabriel Marty, 31042 Toulouse cedex 9, France.
  • Clovis Foguem
    Université de Bourgogne, Centre des Sciences du Goût et de l׳Alimentation(CSGA), UMR 6265 CNRS, UMR 1324 INRA, 9 E Boulevard Jeanne d׳Arc, Dijon 21000, France; Hôpital Auban Moët, Epernay 51200, France.