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Leveraging Machine Learning and Natural Language Processing for Monitoring E-health Publications

Authors:
Andrius Budrionis
Rune Pedersen
Torbjørn Torsvik
Karianne Lind
Omid Saadatfard

Keywords: e-health strategy; publications; machine learning; natural languge processing

Abstract:
E-health is a rapidly developing field governed by national and international guidelines. These guidelines are often generic, making it problematic to monitor the development of the field with regards to the expected directions. To address this shortcoming, we present a data analytics pipeline for continuous monitoring of e-health publications in Norway with regards to the national e-health strategy. The pipeline contains PubMed data import module, machine learning, natural language processing modules and a visualization component. The potential of the proposed approach is illustrated by identifying publication trends in Norway for the last ten years. These trends show how well focus areas of the Norwegian e-health strategy are represented in scientific publications. The pipeline is customizable and can be extended to support other countries, e-health strategies and publication channels.

Pages: 142 to 146

Copyright: Copyright (c) IARIA, 2020

Publication date: March 22, 2020

Published in: conference

ISSN: 2308-4359

ISBN: 978-1-61208-763-4

Location: Valencia, Spain

Dates: from November 21, 2020 to November 25, 2020