2013
DOI: 10.3103/s014768821306004x
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The significance of visual-image presentations for medical intelligent systems

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Cited by 5 publications
(4 citation statements)
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“…Sequence of similar manifestations of the visual image corresponding to one notion can be considered as a fuzzy set or an image row [8] (Figure 1). Differences in individual images will be determined not only by manifestations of pathology, but also by ethnic characteristics of individuals.…”
Section: Fuzzy Image Rowsmentioning
confidence: 99%
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“…Sequence of similar manifestations of the visual image corresponding to one notion can be considered as a fuzzy set or an image row [8] (Figure 1). Differences in individual images will be determined not only by manifestations of pathology, but also by ethnic characteristics of individuals.…”
Section: Fuzzy Image Rowsmentioning
confidence: 99%
“…It is also necessary for expert evaluations to take into account the elements of reflection. The image rows of fuzzy phenotypic changes that were not previously considered as elements of expert systems can offer additional knowledge about diseases [8]. This work stands apart from other studies in the field of fuzzy logic in intelligent systems, with its integrated approach to the assessment of linguistic features and images that incorporates the reflections of experts.…”
Section: Introductionmentioning
confidence: 99%
“…But as can be seen from Figure 1, they are distinguishable, but similar. The fuzziness of transitions between separate representatives of a specific sequence of images permits one to speak about a visual-image quasi-continuum [13,14]. A temporal (dynamic) image series is characterized by how separate images that form it are transformed or metamorphized in time while maintaining them the general and typical.…”
Section: Features Of Representation Of Visual Imagesmentioning
confidence: 99%
“…As a means of formal description of medical knowledge can be viewed frame-based or ontological model. Principle of building a hybrid (linguistic and image-bearing) frame or ontological models that integrate both qualitative and visual image indicators aimed at the formal description of the disease clinical manifestations that have a diagnostic value are reflected in a number of publications [13,14]. Ontology and frame fragments are shown in Figure 2 The figure shows that the domain representing MUCOPOLYSACCHARIDOSIS class includes a number of subclasses (in this example, two of this set).…”
Section: The Formalization Of Linguistic-and-image Modelsmentioning
confidence: 99%