DEEP LEARNING FRAMEWORK FOR RDF AND KNOWLEDGE GRAPHS USING FUZZY MAPS TO SUPPORT MEDICAL DECISION

Main Article Content

HATEM AHMED SAYED AHMED SOLIMAN
FATEMA TABAK

Abstract

The utilize of machine learning as well as data analytics technologies in healthcare are facing fast increase development; the existence of machine learning techniques – such as deep learning – establish a key strength of healthcare fields.

Artificial intelligence with deep learning approaches which offer interactions is able to simulate human behavior. The growing amount of data in semantic web to deal with analysis approaches focusing on big data in health care required to develop, that growth led to the use of the Web Ontology Language (OWL), which is a markup for sharing ontologies on the World Wide Web [1]. OWL was developed as an extension of RDF vocabulary [2] and it’s used in the proposed decision support process. This paper outline Deep Learning Framework for RDF and knowledge Graphs using fuzzy maps to support the medical decision and suggest Diagram approach can be used for implementation.

Keywords:
Deep learning, fuzzy model, healthcare, machine learning, RDF

Article Details

How to Cite
SOLIMAN, H. A. S. A., & TABAK, F. (2020). DEEP LEARNING FRAMEWORK FOR RDF AND KNOWLEDGE GRAPHS USING FUZZY MAPS TO SUPPORT MEDICAL DECISION. Journal of International Research in Medical and Pharmaceutical Sciences, 14(3), 92–97. Retrieved from https://www.ikpresse.com/index.php/JIRMEPS/article/view/4893
Section
Original Research Article

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