Data Driven Knowledge Acquisition Method for Domain Knowledge Enrichment in Healthcare

Sujan Perera; Cory Andrew Henson; Krishnaprasad Thirunarayan; Amit P. Sheth; Suhas Nair

doi:10.1109/BIBM.2012.6392669

Data Driven Knowledge Acquisition Method for Domain Knowledge Enrichment in Healthcare

Sujan Perera, Cory Andrew Henson, Krishnaprasad Thirunarayan, Amit P. Sheth, Suhas Nair

Research output: Contribution to conference › Presentation

Abstract

Semantic computing technologies have matured to be applicable to many critical domains, such as life sciences and health care. However, the key to their success is the rich domain knowledge which consists of domain concepts and relationships, whose creation and refinement remains a challenge. In this paper, we develop a technique for enriching domain knowledge, focusing on populating the domain relationships. We determine missing relationships between the domain concepts by validating domain knowledge against real world data sources. We evaluate our approach in the healthcare domain using Electronic Medical Record(EMR) data, and demonstrate that semantic techniques can be used to semi-automate labour intensive tasks without sacrificing fidelity of domain knowledge.

Original language	American English
Pages	197-204
Number of pages	8
DOIs	https://doi.org/10.1109/BIBM.2012.6392669
State	Published - Oct 1 2012
Event	IEEE International Conference on Bioinformatics & Biomedicine - Duration: Oct 1 2012 → …

Conference

Conference	IEEE International Conference on Bioinformatics & Biomedicine
Period	10/1/12 → …

ASJC Scopus Subject Areas

Biomedical Engineering
Health Informatics

Keywords

Cardiology
Clinical Knowledgebase
Electronic Medical Record
Knowledge Acquisition
Semantic Technology

Disciplines

Bioinformatics
Communication
Communication Technology and New Media
Computer Sciences
Databases and Information Systems
Life Sciences
OS and Networks
Physical Sciences and Mathematics
Science and Technology Studies
Social and Behavioral Sciences

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10.1109/BIBM.2012.6392669License: Unspecified

Cite this

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title = "Data Driven Knowledge Acquisition Method for Domain Knowledge Enrichment in Healthcare",

abstract = "Semantic computing technologies have matured to be applicable to many critical domains, such as life sciences and health care. However, the key to their success is the rich domain knowledge which consists of domain concepts and relationships, whose creation and refinement remains a challenge. In this paper, we develop a technique for enriching domain knowledge, focusing on populating the domain relationships. We determine missing relationships between the domain concepts by validating domain knowledge against real world data sources. We evaluate our approach in the healthcare domain using Electronic Medical Record(EMR) data, and demonstrate that semantic techniques can be used to semi-automate labour intensive tasks without sacrificing fidelity of domain knowledge.",

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AU - Henson, Cory Andrew

AU - Thirunarayan, Krishnaprasad

AU - Sheth, Amit P.

AU - Nair, Suhas

PY - 2012/10/1

Y1 - 2012/10/1

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AB - Semantic computing technologies have matured to be applicable to many critical domains, such as life sciences and health care. However, the key to their success is the rich domain knowledge which consists of domain concepts and relationships, whose creation and refinement remains a challenge. In this paper, we develop a technique for enriching domain knowledge, focusing on populating the domain relationships. We determine missing relationships between the domain concepts by validating domain knowledge against real world data sources. We evaluate our approach in the healthcare domain using Electronic Medical Record(EMR) data, and demonstrate that semantic techniques can be used to semi-automate labour intensive tasks without sacrificing fidelity of domain knowledge.

KW - Cardiology

KW - Clinical Knowledgebase

KW - Electronic Medical Record

KW - Knowledge Acquisition

KW - Semantic Technology

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Data Driven Knowledge Acquisition Method for Domain Knowledge Enrichment in Healthcare

Abstract

Conference

ASJC Scopus Subject Areas

Keywords

Disciplines

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