Combining conceptual graphs and argumentation for aiding in the teleexpertise

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.

Graph-based ontology reasoning for formal verification of BREEAM rules

“…Indeed, on the one hand, it allows the formalization of conceptual and inferential knowledge of a target domain. On the other hand, the provided reasoning tools facilitate the visualization, the enrichment and the verification of the modelled knowledge by end users (Doumbouya, Kamsu-Foguem, Kenfack & Foguem, 2018;Kamsu-Foguem & Tiako, 2017;Doumbouya, Kamsu-Foguem, Kenfack & Foguem, 2015;Kamsu-Foguem & Abanda, 2015;Kamsu-Foguem, Tchuenté-Foguem, & Foguem, 2014;Kamsu-Foguem, Diallo, & Foguem, 2013;Potes Ruiz, Kamsu-Foguem & Noyes, 2013;Kamsu Foguem, Coudert, Béler & Geneste, 2008;Kamsu-Foguem & Chapurlat, 2006;Chein, Mugnier, & Croitoru, 2013). In the context of the semantic web, the conceptual graphs can play a pivotal role for some knowledge representation languages, while ensuring the interoperability and the complementarity of modes of reasoning.…”

Argumentation graphs with constraint-based reasoning for collaborative expertise

“…In this section, we will recall the background of conceptual graphs and constraints drawn from [10]. The argumentation system [5] used in this work is well explained in our previous works [2][3][4]11].…”

“…An effective integration of constraints in collaborative processes must therefore become a central feature of consistent development efforts in argumentative reasoning. In fact, in our previous works [2][3][4], we have modelled collaborative processes between using the Dung argumentation framework, itself represented in conceptual graph formalism which can support the expression of semantic constraints in order to check if there are inconsistencies or not. The solution proposed in this work is to use some laws governing remote medical collaboration that will be modelled as constraints because the laws are obligations and must be respected.…”

“…In our work, the bad attacks represent the attack that starts from one argument to another with greater weight or attacks that do not comply with the guidelines of medical deontology. The detected bad attacks are ignored or removed from the graph of attacks [7,8], then the acceptability semantics are computed on the remaining attacks by using the algorithms proposed in [3].…”

Discovering frequent patterns for in-flight incidents

“…Diagnostic CDSS have as output the type of disease. Many therapeutic CDSS offer a type of care as output (Doumbouya, Kamsu-Foguem, Kenfack, & Foguem, 2015). There are some CDSS that propose care procedures (admission, surgery, discharge) (Huang, Lu, & Duan, 2012), but are not suitable for in-flight medical incident management.…”