Semantic Interoperability in the Securities Industry: Context Interchange Mediation of Semantic Differences in Enumerated Data Types (WEBH)

2003 ◽  
Author(s):  
Allen Moulton ◽  
Stuart E. Madnick ◽  
Michael Siegel
Keyword(s):  
Semantic Interoperability ◽  
Data Types ◽  
Securities Industry

scholarly journals Similarity Analyzer for Semantic Interoperability of Electronic Health Records Using Artificial Intelligence (AI)

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Arjmand Naveed
Keyword(s):  
Artificial Intelligence ◽  
Electronic Health Records ◽  
Semantic Interoperability ◽  
Healthcare Sector ◽  
Data Mapping ◽  
Mapping Data ◽  
Data Types ◽  
Health Records ◽  
Different Types ◽  
Electronic Health

The introduction of Electronic Health Records (EHR) has opened possibilities for solving interoperability issues within the healthcare sector. However, even with the introduction of EHRs, healthcare systems like hospitals and pharmacies remain isolated with no sharing of EHRs due to semantic interoperability issues. This paper extends our previous work in which we proposed a framework that dealt with semantic interoperability and security of EHR. The extension is the proposal of a cloud-based similarity analyzer for data structuring, data mapping, data modeling and conflict removal using Word2vec Artificial Intelligence (AI) technique.  Different types of conflicts are removed from data in order to model data into common data types which can be interpreted by different stakeholders.

Semantic Interoperability Adheres to Proper Models and Code Systems

2010 ◽  
Vol 49 (02) ◽  
pp. 148-155 ◽  
Author(s):  
B. Blobel ◽  
F. Oemig
Keyword(s):  
Semantic Interoperability ◽  
Basic Information ◽  
Data Types ◽  
Advantages And Disadvantages ◽  
Modeling Approaches ◽  
Assessment Systems ◽  
Score Systems ◽  
Attributes Data

Summary Objectives: Achieving semantic interoperability requires not only the use of communication standards like HL7 with its underlying models and specifications, but also to constrain those models to instances including permitted attributes, data types, values and code systems. Even the application of both strategies may lead to different modeling approaches and therefore incompatible results, however. Methods: This paper analyzes the different ways to create a model exemplified at score and assessment systems. Results: The different approaches have advantages and disadvantages. The presented results allow for transmitting the same basic information facilitating HL7 v2.x and V3 in a way reducing implementation efforts. Conclusions: Establishing a generic approach to communicate the details of score systems driven by an appropriate set of codes is the best solution for implementers.

scholarly journals Section 2: Patient Records: Electronic Patient Records: Moving from Islands and Bridges towards Electronic Health Records for Continuity of Care

2007 ◽  
Vol 16 (01) ◽  
pp. 34-46 ◽  
Author(s):  
Oliver Bott ◽  
Christian Kohl ◽  
Christian Lovis ◽  
Sebastian Garde ◽  
Petra Knaup
Keyword(s):  
Quality Care ◽  
Health Data ◽  
Semantic Interoperability ◽  
Content Standards ◽  
Patient Records ◽  
Electronic Patient Records ◽  
Data Types ◽  
Use Of Resources ◽  
Patient Will ◽  
Consensus Standard

SummaryElectronic patient record (EPR) systems are increasingly used and have matured sufficiently so as to contribute to high quality care and efficient patient management. Our objective is to summarize current trends and major achievements in the field of EPR in the last year and to discuss their future prospects.Integrating health data from a variety of sources in a comprehensive EPR is a major prerequisite for e-health and eresearch. Current research continues to elaborate architectures, technologies and security concepts. To achieve semantic interoperability standards are developed on different levels, including basic data types, messages, services, architectures, terminologies, ontologies, scope and presentation of EPR content. Standards development organisations have started to harmonize their work to arrive at a consensus standard for EPR systems. Integrating the health care enterprise as a whole will optimize efficient use of resources, logistics and scheduling.The past few years have seen a myriad of developments of EPR systems. However, it is still a long way, until EPR systems can flexibly fulfill all user requirements and an EHR will become broadly accepted. Semantic interoperability will be a key to successful EPR use, especially to avoid double data entries and to better integrate data recording within local workflows. The patient will become an empowered partner, not only by giving him access to his health data. All this will result in enormous quantities of data. Thus, time has come to determine how relevant data can be presented to the stakeholders adequately.

scholarly journals An Extended Semantic Interoperability Model for Distributed Electronic Health Record Based on Fuzzy Ontology Semantics

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1733
Author(s):  
Ebtsam Adel ◽  
Shaker El-Sappagh ◽  
Sherif Barakat ◽  
Jong-Wan Hu ◽  
Mohammed Elmogy
Keyword(s):  
Electronic Health Record ◽  
Real Data ◽  
Semantic Interoperability ◽  
Health Record ◽  
Data Types ◽  
Fuzzy Ontology ◽  
Input Source ◽  
Electronic Health ◽  
Learning Projects ◽  
Mimic Iii

Semantic interoperability of distributed electronic health record (EHR) systems is a crucial problem for querying EHR and machine learning projects. The main contribution of this paper is to propose and implement a fuzzy ontology-based semantic interoperability framework for distributed EHR systems. First, a separate standard ontology is created for each input source. Second, a unified ontology is created that merges the previously created ontologies. However, this crisp ontology is not able to answer vague or uncertain queries. We thirdly extend the integrated crisp ontology into a fuzzy ontology by using a standard methodology and fuzzy logic to handle this limitation. The used dataset includes identified data of 100 patients. The resulting fuzzy ontology includes 27 class, 58 properties, 43 fuzzy data types, 451 instances, 8376 axioms, 5232 logical axioms, 1216 declarative axioms, 113 annotation axioms, and 3204 data property assertions. The resulting ontology is tested using real data from the MIMIC-III intensive care unit dataset and real archetypes from openEHR. This fuzzy ontology-based system helps physicians accurately query any required data about patients from distributed locations using near-natural language queries. Domain specialists validated the accuracy and correctness of the obtained results.

Rationale and Design Considerations for a Semantic Mediator in Health Information Systems

1998 ◽  
Vol 37 (04/05) ◽  
pp. 518-526 ◽  
Author(s):  
D. Sauquet ◽  
M.-C. Jaulent ◽  
E. Zapletal ◽  
M. Lavril ◽  
P. Degoulet
Keyword(s):  
Information Systems ◽  
Software Engineering ◽  
Health Information ◽  
Rapid Development ◽  
Heterogeneous Systems ◽  
Health Information Systems ◽  
Semantic Interoperability ◽  
Point Of View ◽  
Current State ◽  
Engineering Environment

AbstractRapid development of community health information networks raises the issue of semantic interoperability between distributed and heterogeneous systems. Indeed, operational health information systems originate from heterogeneous teams of independent developers and have to cooperate in order to exchange data and services. A good cooperation is based on a good understanding of the messages exchanged between the systems. The main issue of semantic interoperability is to ensure that the exchange is not only possible but also meaningful. The main objective of this paper is to analyze semantic interoperability from a software engineering point of view. It describes the principles for the design of a semantic mediator (SM) in the framework of a distributed object manager (DOM). The mediator is itself a component that should allow the exchange of messages independently of languages and platforms. The functional architecture of such a SM is detailed. These principles have been partly applied in the context of the HEllOS object-oriented software engineering environment. The resulting service components are presented with their current state of achievement.

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