State of the Art of Semantic Web for Healthcare

Zenuni, Xhemal; Raufi, Bujar; Ismaili, Florije; Ajdari, Jaumin

doi:10.1016/j.sbspro.2015.06.213

Cited by 47 publications

(22 citation statements)

References 9 publications

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“…The result of this work is a conceptual structure called “ontology”, which is a computer-processable representation of this expert knowledge [ 18 ]. An ontology consists of a hierarchy of concepts that represent the terms used in the domain being modeled, the relationships that hold between them, and a series of logic clauses and/or rules for defining new concepts, properties or relationships.…”

Section: Initial Application For Automating Sna Studies On Alcoholmentioning

confidence: 99%

A Semantic Social Network Analysis Tool for Sensitivity Analysis and What-If Scenario Testing in Alcohol Consumption Studies

Benítez-Andrades

Rodríguez-González

Benavides

et al. 2018

IJERPH

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Social Network Analysis (SNA) is a set of techniques developed in the field of social and behavioral sciences research, in order to characterize and study the social relationships that are established among a set of individuals. When building a social network for performing an SNA analysis, an initial process of data gathering is achieved in order to extract the characteristics of the individuals and their relationships. This is usually done by completing a questionnaire containing different types of questions that will be later used to obtain the SNA measures needed to perform the study. There are, then, a great number of different possible network-generating questions and also many possibilities for mapping the responses to the corresponding characteristics and relationships. Many variations may be introduced into these questions (the way they are posed, the weights given to each of the responses, etc.) that may have an effect on the resulting networks. All these different variations are difficult to achieve manually, because the process is time-consuming and error-prone. The tool described in this paper uses semantic knowledge representation techniques in order to facilitate this kind of sensitivity studies. The base of the tool is a conceptual structure, called “ontology” that is able to represent the different concepts and their definitions. The tool is compared to other similar ones, and the advantages of the approach are highlighted, giving some particular examples from an ongoing SNA study about alcohol consumption habits in adolescents.

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Section: Initial Application For Automating Sna Studies On Alcoholmentioning

confidence: 99%

A Semantic Social Network Analysis Tool for Sensitivity Analysis and What-If Scenario Testing in Alcohol Consumption Studies

Benítez-Andrades

Rodríguez-González

Benavides

et al. 2018

IJERPH

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“…The effective outcome of this would be, knowledge dissemination associated with existing ontologies will be further improved, enhancing the reusability aspects as well. Additionally, it will prevent a precious piece of information resource being stagnated on the internet after serving, only the one specific purpose it had been created for, which is recognized as an utmost cognitive waste as well by [21].…”

Section: Introductionmentioning

confidence: 99%

Domain and Schema Independent Semantic Model Verbalization: A Conceptual Overview

Vidanage¹,

Maizura²,

Mohemad³

et al. 2019

IJACSA

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Semantic Web-based technologies have become extremely popular and its a success that has spread across many domains, additional to the computer science domain. Nevertheless, the reusability aspects associated with the created and available semantic knowledge models are very low. The main bottleneck associated with this issue is, the difficulty associated in understanding the complex schema of a knowledge model created and barriers associated with querying the knowledge models using SPARQL or SQWRL query formulations. This research emphasizes on proposing a verbalizer which can go beyond existing Controlled Natural Language (CNL) type verbalizers and to verbalizer knowledge stored in a knowledge model file written in either RDF or OWL format, despite its domain and schematics.

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“…LOD is a new Semantic Web set of best practice of standards to publish and link heterogeneous data. It can be applied to the representation and management of public level health data to alleviate such challenges [5,6,7].…”

Section: Introductionmentioning

confidence: 99%

LOD Development System for Medical Information Standard

Moon¹,

Han²,

An³

2018

IJET

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This paper describes Linked Open Data(LOD) development system and its application of medical information standard as Observational Medical Outcomes Partnership(OMOP) Common Data Model(CDM). The OMOP CDM allows for the systematic analysis of disparate observational database in each hospital. This paper describes a LOD instance development system based on SII. It can generate the application-specified instance development system automatically. Therefore, we applied by medical information standard as OMOP CDM to LOD development system. As a result, it was confirmed that there is no problem in applying to the standardization of medical information using the LOD development system.

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State of the Art of Semantic Web for Healthcare

Cited by 47 publications

References 9 publications

A Semantic Social Network Analysis Tool for Sensitivity Analysis and What-If Scenario Testing in Alcohol Consumption Studies

A Semantic Social Network Analysis Tool for Sensitivity Analysis and What-If Scenario Testing in Alcohol Consumption Studies

Domain and Schema Independent Semantic Model Verbalization: A Conceptual Overview

LOD Development System for Medical Information Standard

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