Conceptual graph operations for formal visual reasoning in the medical domain |
| |
| Affiliation: | 1. Laboratory of Production Engineering (LGP), EA 1905, ENIT-INPT University of Toulouse, 47, avenue d’Azereix, BP 1629, 65016 Tarbes cedex, France;2. MAT Laboratory, UMI 209, Unit for Mathematical and Computer Modeling of Complex Systems - UMMISCO, Faculty of Science, University of Yaoundé I, PO Box 812, Yaoundé, Cameroon;3. Center for Food and Taste sciences (CSGA), UMR 6265 CNRS, UMR 1324 INRA, University of Burgundy, 9 E, boulevard Jeanne-d’Arc, 21000 Dijon, France;1. Biophysics laboratory LTIM-LR12ES06, faculty of medicine of Monastir, university of Monastir, 5019 Monastir, Tunisia;2. CRISTAL laboratory, ENSI, research group in forms and images of Tunisia (GRIFT), university of Manouba, 2010 Manouba, Tunisia;1. Centre for Medical Image Computing, Medical Physics and Bioengineering Department, University College London, WC1E BT London, UK;2. Grupo Imagine, Grupo de Ingeniería Biomédica, Universidad de los Andes, Bogotá, Colombia;3. Université de Lyon, CREATIS; CNRS UMR5220; Inserm U1044; INSA-Lyon; Université Lyon 1, France;1. UPMC University Paris 06, UMR 7371, UMR_S 1146, Laboratoire d’Imagerie Biomédicale, 75006 Paris, France;2. CNRS, UMR 7371, Laboratoire d’Imagerie Biomédicale, 75006 Paris, France;3. INSERM, UMR S 1146, Laboratoire d’Imagerie Biomédicale, 75006 Paris, France;1. Department of Cybernetics and Biomedical Engineering, VSB–Technical University of Ostrava, 17. listopadu 15, Ostrava Poruba 708 33, Czech Republic;2. Biomedical Sensors Group, University of Lyon, Institute for Nanotechnology of Lyon, UMR CNRS 5270 INL – INSA Lyon, 69100 Villeurbanne, France;1. Universidad Nacional de Rosario, Av. Pellegrini 250, S2000BTP Rosario, Argentina;2. ICube/INSA de Strasbourg, 300, boulevard Sébastien Brant, CS 10413, F- 67412 Illkirch cedex, France;3. LGeCo/INSA de Strasbourg, 24 boulevard de la Victoire, 67084 Strasbourg, France |
| |
| Abstract: | ObjectiveConceptual graphs (CGs) are used to represent clinical guidelines because they support visual reasoning with a logical background, making them a potentially valuable representation for guidelines.Materials and methodsConceptual graph formalism has an essential and basic component: a formal vocabulary that drives all of the other mechanisms, notably specialization and projection. The graph's theoretical operations, such as projection, rules, derivation, constraints, probabilities and uncertainty, support diagrammatic reasoning.ResultsA conceptual graph's graphical user interface includes a multilingual vocabulary management, some query and decision-making facilities and visual graph representations that are simple and interesting for user interactions. The described proposition using the Conceptual Graph user interface (CoGui) improves the performance of the actors in the diagnostic context of heart failure with preserved ejection fraction.DiscussionCGs capture the essential features of the medical processes underlying clinical reasoning. CGs are indeed useful as a way for the physician to represent guidelines, and well-defined semantic representations allow users to have a maximal understanding of the knowledge reasoning process.ConclusionCG operations of visual representations that uncover some of the actual complexities of clinicians’ reasoning have been tested in clinical guideline comprehension and used to translate text and diagrammatic guidelines into computer interpretable representations. |
| |
| Keywords: | Knowledge representation Conceptual graphs Visual reasoning Formal semantics Clinical guidelines and protocols Heart failure |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
