عنوان
پدید آورنده
موضوع
رده
کتابخانه
محل استقرار
NATIONAL BIBLIOGRAPHY NUMBER
Number
TLpq2276872361
LANGUAGE OF THE ITEM
.Language of Text, Soundtrack etc
انگلیسی
TITLE AND STATEMENT OF RESPONSIBILITY
Title Proper
Automated Disease-drug Ontology Generation Framework Powered by Linked Biomedical Ontologies
General Material Designation
[Thesis]
First Statement of Responsibility
Alobaidi, Mazen
Subsequent Statement of Responsibility
Malik, Khalid
.PUBLICATION, DISTRIBUTION, ETC
Name of Publisher, Distributor, etc.
Oakland University
Date of Publication, Distribution, etc.
2019
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
125
DISSERTATION (THESIS) NOTE
Dissertation or thesis details and type of degree
Ph.D.
Body granting the degree
Oakland University
Text preceding or following the note
2019
SUMMARY OR ABSTRACT
Text of Note
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.
TOPICAL NAME USED AS SUBJECT
Computer science
Information science
PERSONAL NAME - PRIMARY RESPONSIBILITY
Alobaidi, Mazen
Malik, Khalid
ELECTRONIC LOCATION AND ACCESS
Electronic name
مطالعه متن کتاب p
[Thesis]
276903
a
Y
