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Linking physicians to medical research results via knowledge graph embeddings and twitter

 
: Sadeghi, A.; Lehmann, J.

:

Cellier, P.:
Machine Learning and Knowledge Discovery in Databases. Proceedings. Pt.I : International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019
Cham: Springer Nature, 2020 (Communications in computer and information science 1167)
ISBN: 978-3-030-43822-7 (Print)
ISBN: 978-3-030-43823-4 (Online)
pp.622-630
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) <2019, Würzburg>
English
Conference Paper
Fraunhofer IAIS ()

Abstract
Informing professionals about the latest research results in their field is a particularly important task in the field of health care, since any development in this field directly improves the health status of the patients. Meanwhile, social media is an infrastructure that allows public instant sharing of information, thus it has recently become popular in medical applications. In this study, we apply Multiple Distance Knowledge Graph Embeddings (MDE) to link physicians and surgeons to the latest medical breakthroughs that are shared as the research results on Twitter. Our study shows that using this method physicians can be informed about the new findings in their field given that they have an account dedicated to their profession.

: http://publica.fraunhofer.de/documents/N-596166.html