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Using Semantic Knowledge to Enhance ...

Hendawi, Rasha,

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Using Semantic Knowledge to Enhance Healthcare /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Using Semantic Knowledge to Enhance Healthcare // Rasha Hendawi.
Author:	Hendawi, Rasha,
Description:	1 electronic resource (186 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-03, Section: A.
Contained By:	Dissertations Abstracts International86-03A.
Subject:	Computer science. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31298831
ISBN:	9798384101482

Using Semantic Knowledge to Enhance Healthcare /
Hendawi, Rasha,

Using Semantic Knowledge to Enhance Healthcare /Rasha Hendawi. - 1 electronic resource (186 pages)

Source: Dissertations Abstracts International, Volume: 86-03, Section: A.

Intelligent healthcare services and biomedical products rely on the ability to effectively utilize valuable medical data. However, although there is a large amount of medical data generated from electronic health record (EHR), social media, medical devices, labs, etc., their unstructured, heterogeneous, and distributed nature makes using them incredibly challenging. Nowadays, Semantic Web technologies have been proposed to provide a common framework for data sharing and reusing across application, platforms, locations, and organizations. They are enabling computers to better manipulate information on human's behalf. Semantic Web technologies have been used in healthcare domain to provide usable knowledge for healthcare, but its development is still in the infancy stage. In this research, we have proposed effective approaches of applying semantic web technologies to healthcare to provide intelligent personalized healthcare services to patients. We designed semantic web-enabled knowledge frameworks that can understand, integrate, link, analyze, and execute a wealth of acquired medical data. It generates actionable knowledge from health data sources, thus improving healthcare by allowing for more accurate diagnosis, illness prevention, individualized therapy, health recommendations and better decision-making. The medical applications we developed based on these knowledge frameworks, including medical ontologies, personalized healthcare recommendation systems, medical annotation systems, medical terms explanation systems, artificial intelligent explanation system and personalized health knowledge graph. These systems provide high-quality personalized context-aware medical services to patients. They can work as pilot example systems for researchers and stakeholders in this domain.

English

ISBN: 9798384101482Subjects--Topical Terms:

523869
Computer science.
Subjects--Index Terms:

Entity recognition

Using Semantic Knowledge to Enhance Healthcare /
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245 1 0 $a Using Semantic Knowledge to Enhance Healthcare / $c Rasha Hendawi.
264 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2024
300 $a 1 electronic resource (186 pages)
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500 $a Source: Dissertations Abstracts International, Volume: 86-03, Section: A.
500 $a Advisors: Li, Juan Committee members: Magel, Ken; Myronovych, Oksana; Jiang, Long.
502 $b Ph.D. $c North Dakota State University $d 2024.
520 $a Intelligent healthcare services and biomedical products rely on the ability to effectively utilize valuable medical data. However, although there is a large amount of medical data generated from electronic health record (EHR), social media, medical devices, labs, etc., their unstructured, heterogeneous, and distributed nature makes using them incredibly challenging. Nowadays, Semantic Web technologies have been proposed to provide a common framework for data sharing and reusing across application, platforms, locations, and organizations. They are enabling computers to better manipulate information on human's behalf. Semantic Web technologies have been used in healthcare domain to provide usable knowledge for healthcare, but its development is still in the infancy stage. In this research, we have proposed effective approaches of applying semantic web technologies to healthcare to provide intelligent personalized healthcare services to patients. We designed semantic web-enabled knowledge frameworks that can understand, integrate, link, analyze, and execute a wealth of acquired medical data. It generates actionable knowledge from health data sources, thus improving healthcare by allowing for more accurate diagnosis, illness prevention, individualized therapy, health recommendations and better decision-making. The medical applications we developed based on these knowledge frameworks, including medical ontologies, personalized healthcare recommendation systems, medical annotation systems, medical terms explanation systems, artificial intelligent explanation system and personalized health knowledge graph. These systems provide high-quality personalized context-aware medical services to patients. They can work as pilot example systems for researchers and stakeholders in this domain.
546 $a English
590 $a School code: 0157
650 4 $a Computer science. $3 523869
650 4 $a Biomedical engineering. $3 535387
650 4 $a Biostatistics. $3 1002712
650 4 $a Information science. $3 554358
653 $a Entity recognition
653 $a Healthcare services
653 $a Knowledge graph
653 $a Ontology
653 $a Semantic web technologies
690 $a 0984
690 $a 0541
690 $a 0769
690 $a 0308
690 $a 0723
710 2 $a North Dakota State University. $b Computer Science. $e degree granting institution. $3 3816183
720 1 $a Li, Juan $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 86-03A.
790 $a 0157
791 $a Ph.D.
792 $a 2024
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31298831