Literature DB >> 22640816

Semantic patient information aggregation and medicinal decision support.

Pieterjan De Potter1, Hans Cools, Kristof Depraetere, Giovanni Mels, Pedro Debevere, Jos De Roo, Csaba Huszka, Dirk Colaert, Erik Mannens, Rik Van de Walle.   

Abstract

Although the health care sector has already been subjected to a major computerization effort, this effort is often limited to the implementation of standalone systems which do not communicate with each other. Interoperability problems limit health care applications from achieving their full potential. In this paper, we propose the use of Semantic Web technologies to solve interoperability problems between data providers. Through the development of unifying health care ontologies, data from multiple health care providers can be aggregated, which can then be used as input for a decision support system. This way, more data is taken into account than a single health care provider possesses in his local setting. The feasibility of our approach is demonstrated by the creation of an end-to-end proof of concept, focusing on Belgian health care providers and medicinal decision support.
Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

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Year:  2012        PMID: 22640816     DOI: 10.1016/j.cmpb.2012.04.002

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  4 in total

1.  An adaptive semantic based mediation system for data interoperability among Health Information Systems.

Authors:  Wajahat Ali Khan; Asad Masood Khattak; Maqbool Hussain; Muhammad Bilal Amin; Muhammad Afzal; Christopher Nugent; Sungyoung Lee
Journal:  J Med Syst       Date:  2014-06-26       Impact factor: 4.460

2.  Using Compact Coevolutionary Algorithm for Matching Biomedical Ontologies.

Authors:  Xingsi Xue; Jie Chen; Junfeng Chen; Dongxu Chen
Journal:  Comput Intell Neurosci       Date:  2018-10-08

3.  Interactive biomedical ontology matching.

Authors:  Xingsi Xue; Zhi Hang; Zhengyi Tang
Journal:  PLoS One       Date:  2019-04-17       Impact factor: 3.240

4.  Matching Biomedical Ontologies via a Hybrid Graph Attention Network.

Authors:  Peng Wang; Yunyan Hu
Journal:  Front Genet       Date:  2022-07-22       Impact factor: 4.772

  4 in total

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