Automated Disease-drug Ontology Generation Framework Powered by Linked Biomedical Ontologies

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" Automated Disease-drug Ontology Generation Framework Powered by Linked Biomedical Ontologies "
Alobaidi, Mazen Malik, Khalid

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	1051784
Doc. No	:	TL50901
Main Entry	:	Alobaidi, Mazen
Title & Author	:	Automated Disease-drug Ontology Generation Framework Powered by Linked Biomedical Ontologies\ Alobaidi, MazenMalik, Khalid
College	:	Oakland University
Date	:	2019
Degree	:	Ph.D.
student score	:	2019
Note	:	125 p.
Abstract	:	The exponential growth of unstructured data available in the biomedical literature and electronic health records requires powerful technologies and novel architectures. The success of smart healthcare applications in clinical decision support, disease diagnosis, and healthcare management depends on knowledge representation that is interpretable by machines in order to infer new knowledge from. To this end, ontological data models are expected to play a pivotal role in organizing, integrating, and representing knowledge machines can understand and act upon. Unfortunately, constructing such models using non-automated means can be prohibitively time-consuming for both domain experts and ontology engineers, thereby limiting the scale and/or the scope of the required ontological models.
Descriptor	:	Computer science
	:	Information science
Added Entry	:	Malik, Khalid
Added Entry	:	Oakland University