An iconic language for the graphical representation of medical concepts

<p>Abstract</p> <p>Background</p> <p>Many medication errors are encountered in drug prescriptions, which would not occur if practitioners could remember the drug properties. They can refer to drug monographs to find these properties, however drug monographs are long and tedious to read during consultation. We propose a two-step approach for facilitating access to drug monographs. The first step, presented here, is the design of a graphical language, called VCM.</p> <p>Methods</p> <p>The VCM graphical language was designed using a small number of graphical primitives and combinatory rules. VCM was evaluated over 11 volunteer general practitioners to assess if the language is easy to learn, to understand and to use. Evaluators were asked to register their VCM training time, to indicate the meaning of VCM icons and sentences, and to answer clinical questions related to randomly generated drug monograph-like documents, supplied in text or VCM format.</p> <p>Results</p> <p>VCM can represent the various signs, diseases, physiological states, life habits, drugs and tests described in drug monographs. Grammatical rules make it possible to generate many icons by combining a small number of primitives and reusing simple icons to build more complex ones. Icons can be organized into simple sentences to express drug recommendations. Evaluation showed that VCM was learnt in 2 to 7 hours, that physicians understood 89% of the tested VCM icons, and that they answered correctly to 94% of questions using VCM (versus 88% using text, <it>p </it>= 0.003) and 1.8 times faster (<it>p </it>< 0.001).</p> <p>Conclusion</p> <p>VCM can be learnt in a few hours and appears to be easy to read. It can now be used in a second step: the design of graphical interfaces facilitating access to drug monographs. It could also be used for broader applications, including the design of interfaces for consulting other types of medical document or medical data, or, very simply, to enrich medical texts.</p

A semi-automatic semantic method for mapping SNOMED CT concepts to VCM Icons

VCM (Visualization of Concept in Medicine) is an iconic language for representing key medical concepts by icons. However, the use of this language with reference terminologies, such as SNOMED CT, will require the mapping of its icons to the terms of these terminologies. Here, we present and evaluate a semi-automatic semantic method for the mapping of SNOMED CT concepts to VCM icons. Both SNOMED CT and VCM are compositional in nature; SNOMED CT is expressed in description logic and VCM semantics are formalized in an OWL ontology. The proposed method involves the manual mapping of a limited number of underlying concepts from the VCM ontology, followed by automatic generation of the rest of the mapping. We applied this method to the clinical findings of the SNOMED CT CORE subset, and 100 randomly-selected mappings were evaluated by three experts. The results obtained were promising, with 82 of the SNOMED CT concepts correctly linked to VCM icons according to the experts. Most of the errors were easy to fix

Using graph transformation algorithms to generate natural language equivalents of icons expressing medical concepts

A graphical language addresses the need to communicate medical information in a synthetic way. Medical concepts are expressed by icons conveying fast visual information about patients' current state or about the known effects of drugs. In order to increase the visual language's acceptance and usability, a natural language generation interface is currently developed. In this context, this paper describes the use of an informatics method ---graph transformation--- to prepare data consisting of concepts in an OWL-DL ontology for use in a natural language generation component. The OWL concept may be considered as a star-shaped graph with a central node. The method transforms it into a graph representing the deep semantic structure of a natural language phrase. This work may be of future use in other contexts where ontology concepts have to be mapped to half-formalized natural language expressions.Comment: Presented at the TSD 2014 conference: Text, Speech and Dialogue, 17th international conference. Brno, Czech Republic, September 8-12, 2014. 10 pages, 7 figure

Anatomical ontologies: names and places in biology

Ontology has long been the preserve of philosophers and logicians. Recently, ideas from this field have been picked up by computer scientists as a basis for encoding knowledge and with the hope of achieving interoperability and intelligent system behavior. In bioinformatics, ontologies might allow hitherto impossible query and data-mining activities. We review the use of anatomy ontologies to represent space in biological organisms, specifically mouse and human

Visual Programming: Concepts and Implementations

The computing environment has changed dramatically since the advent of the computer. Enhanced computer graphics and sheer processing power have ushered in a new age of computing. User interfaces have advanced from simple line entry to powerful graphical interfaces. With these advances, computer languages are no longer forced to be sequentially and textually-based. A new programming paradigm has evolved to harness the power of today's computing environment - visual programming. Visual programming provides the user with visible models which reflect physical objects. By connecting these visible models to each other, an executable program is created. By removing the inherent abstractions of textual languages, visual programming could lead computing into a new era

Communicating content: development and evaluation of icons for academic document triage through visualisation and perception

This work seeks to identify key features and characteristics for the design of icons that can support the tasks of information seekers in academic document triage interfaces. Such icons are meant to act as visual links to the specific elements or sections in an academic document. We suggest that icons in triage interfaces are better able to communicate information, provide feedback and enable faster user interactions than text, particularly in mobile-based interfaces. Through investigation of visualisation and perception processes, we are able to propose five primary icon categories, the two most dominant being iconic and symbolic: iconic representations mostly apply to graphically and spatially distinct document elements (i.e. Title, Abstract, Tables and Figures), externalising the elements’ surface propositions. Symbolic representations are largely associated with elements of greater semantic value (Introduction, Conclusion, Full text and Author), drawing upon the elements’ deep propositions

A study of spatial data models and their application to selecting information from pictorial databases

People have always used visual techniques to locate information in the space surrounding them. However with the advent of powerful computer systems and user-friendly interfaces it has become possible to extend such techniques to stored pictorial information. Pictorial database systems have in the past primarily used mathematical or textual search techniques to locate specific pictures contained within such databases. However these techniques have largely relied upon complex combinations of numeric and textual queries in order to find the required pictures. Such techniques restrict users of pictorial databases to expressing what is in essence a visual query in a numeric or character based form. What is required is the ability to express such queries in a form that more closely matches the user's visual memory or perception of the picture required. It is suggested in this thesis that spatial techniques of search are important and that two of the most important attributes of a picture are the spatial positions and the spatial relationships of objects contained within such pictures. It is further suggested that a database management system which allows users to indicate the nature of their query by visually placing iconic representations of objects on an interface in spatially appropriate positions, is a feasible method by which pictures might be found from a pictorial database. This thesis undertakes a detailed study of spatial techniques using a combination of historical evidence, psychological conclusions and practical examples to demonstrate that the spatial metaphor is an important concept and that pictures can be readily found by visually specifying the spatial positions and relationships between objects contained within them

Building a Know-How and Knowing-That Cartography to Enhance KM Processes in a Healthcare Setting

While knowledge management (KM) is becoming an established discipline with many applications and techniques, its adoption in healthcare has been challenging. It facilitates the creation, identification, acquisition, development, preservation, dissemination, and finally utilization of various facets of a healthcare enterprise’s knowledge assets. Knowledge identification and preservation are two facets of knowledge capitalization’s operations. Knowledge cartography is used nowadays as a tool for knowledge identification, sharing, and decision support. In this paper, we propose a Know-How and Knowing-That cartography for Healthcare Information System (HIS) and clinical decision support in the context of the organization of protection of the motor disabled children of Sfax-Tunisia (ASHMS). In fact, this cartography enables decision makers with general and detailed visibility of Know-How and Knowing-That mobilized in the ASHMS. It also facilitates clinical decision support by proposing the most appropriate alternatives for the continued treatment (or cessation) of each motor disabled child receiving treatment