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Authors: Christian Nawroth ; Felix Engel ; Tobias Eljasik-Swoboda and Matthias L. Hemmje

Affiliation: Lehrgebiet Multimedia und Internetanwendungen, FernUniversität in Hagen, Universitätsstraße 47, Hagen and Germany

ISBN: 978-989-758-318-6

Keyword(s): Emerging Named Entity Recognition, Data Science, Natural Language Processing, Information Retrieval, Clinical Argumentation Support.

Related Ontology Subjects/Areas/Topics: Applications ; Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Business Analytics ; Cardiovascular Technologies ; Computational Intelligence ; Computing and Telecommunications in Cardiology ; Data Analytics ; Data Engineering ; Data Management and Quality ; Decision Support Systems ; Decision Support Systems, Remote Data Analysis ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Information Retrieval ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Ontologies and the Semantic Web ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Software Engineering ; Support Vector Machines and Applications ; Symbolic Systems ; Text Analytics ; Theory and Methods

Abstract: In this paper we discuss the challenges of growing amounts of clinical literature for medical staff. We introduce our concepts emerging Named Entity (eNE) and emerging Named Entity Recognition (eNER) and show the results of an empirical study on the incidence of eNEs in the PubMed document set, which is the main contribution of this article. We discuss how emerging Named Entities can be used for Argumentation Support, Information Retrieval (IR) Support and Trend Analysis in Clinical Virtual Research Environments (VREs) dealing with large amounts of medical literature. Based on the empirical study and the discussion we derive use cases and a data science and user-feedback based architecture for the detection and the use of eNEs for IR and Argumentation Support in clinical VREs, like the related project RecomRatio.

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Paper citation in several formats:
Nawroth, C.; Engel, F.; Eljasik-Swoboda, T. and L. Hemmje, M. (2018). Towards Enabling Emerging Named Entity Recognition as a Clinical Information and Argumentation Support.In Proceedings of the 7th International Conference on Data Science, Technology and Applications - Volume 1: DATA, ISBN 978-989-758-318-6, pages 47-55. DOI: 10.5220/0006853200470055

@conference{data18,
author={Christian Nawroth. and Felix Engel. and Tobias Eljasik{-}Swoboda. and Matthias L. Hemmje.},
title={Towards Enabling Emerging Named Entity Recognition as a Clinical Information and Argumentation Support},
booktitle={Proceedings of the 7th International Conference on Data Science, Technology and Applications - Volume 1: DATA,},
year={2018},
pages={47-55},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006853200470055},
isbn={978-989-758-318-6},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Data Science, Technology and Applications - Volume 1: DATA,
TI - Towards Enabling Emerging Named Entity Recognition as a Clinical Information and Argumentation Support
SN - 978-989-758-318-6
AU - Nawroth, C.
AU - Engel, F.
AU - Eljasik-Swoboda, T.
AU - L. Hemmje, M.
PY - 2018
SP - 47
EP - 55
DO - 10.5220/0006853200470055

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