ABSTRACT
SUMMARY: In public health research and more precisely in the reuse of electronic health data, selecting patients, identifying specific events and interpreting results typically requires biomedical knowledge. The queryMed R package aims to facilitate the integration of medical and pharmacological knowledge stored in formats compliant with the Linked Data paradigm (e.g. OWL ontologies and RDF datasets) into the R statistical programming environment. We show how it allowed us to identify all the drugs prescribed for critical limb ischemia (CLI) and also to detect one contraindicated prescription for one patient by linking a medical database of 1003 CLI patients to ontologies. AVAILABILITY AND IMPLEMENTATION: queryMed is readily usable for medical data mappings and enrichment. Sources, R vignettes and test data are available on GitHub (https://github.com/yannrivault/queryMed) and are archived on Zenodo (https://doi.org/10.5281/zenodo.1323481).
Subject(s)
Semantic Web , Data Management , Databases, Factual , HumansABSTRACT
The goal of this article is to present to the radiologist the different theories of the sign and their consequences for sign representation in computer systems. All the theories of the sign are presented, but the most relevant are highlighted in order to explain the great modeling systems currently in use (such as DICOM-SR or the UMLS). The constructivist approach of the notion of disease, the semiosis process, which starting from signs produces new signs, and the structuralist analysis of sign through language are emphasized. The purpose of this analysis is to end up with a consensual representation of the sign that can be understood by human beings and processed by machines. Such a representation, also known as an ontology, is based on a semantic organization of language, thus allowing medicine to become a truly scientific discipline. It aims at disambiguating the symbols given to machines, which will help us in our reasoning.
Subject(s)
Radiographic Image Interpretation, Computer-Assisted , Radiography , HumansABSTRACT
The human cerebral cortex anatomy describes the brain organization at the scale of gyri and sulci. It is used as landmarks for neurosurgery as well as localization support for functional data analysis or inter-subject data comparison. Existing models of the cortex anatomy either rely on image labeling but fail to represent variability and structural properties or rely on a conceptual model but miss the inner 3D nature and relations of anatomical structures. This study was therefore conducted to propose a model of sulco-gyral anatomy for the healthy human brain. We hypothesized that both numeric knowledge (i.e., image-based) and symbolic knowledge (i.e., concept-based) have to be represented and coordinated. In addition, the representation of this knowledge should be application-independent in order to be usable in various contexts. Therefore, we devised a symbolic model describing specialization, composition and spatial organization of cortical anatomical structures. We also collected numeric knowledge such as 3D models of shape and shape variation about cortical anatomical structures. For each numeric piece of knowledge, a companion file describes the concept it refers to and the nature of the relationship. Demonstration software performs a mapping between the numeric and the symbolic aspects for browsing the knowledge base.
Subject(s)
Cerebral Cortex/anatomy & histology , Databases as Topic , Medical Illustration , Humans , Hypermedia , Imaging, Three-Dimensional , Language , Magnetic Resonance Imaging , Neuroanatomy , Programming Languages , Terminology as TopicABSTRACT
Advances in software, networking, and imaging technology provide a unique opportunity for developing information systems in anatomy that can deliver relevant knowledge to the clinicians, researchers, educators, and students. Recent software tools initially produced for graphic imaging are now available in the medical graphic design field. The authors describe an original method they used to create electronic images of the central nervous system and its coverings with photo-realistic rendering. They present preliminary results and discuss the potential of this new technique as a teaching tool for neuroanatomy.
