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Using Data Mining to Investigate Hos...

Al-Shanableh, Najah.

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Using Data Mining to Investigate Hospitalization Experiences of Parkinson's Disease Patients.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Using Data Mining to Investigate Hospitalization Experiences of Parkinson's Disease Patients./
Author:	Al-Shanableh, Najah.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:	167 p.
Notes:	Source: Dissertations Abstracts International, Volume: 80-05, Section: B.
Contained By:	Dissertations Abstracts International80-05B.
Subject:	Information Technology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10988642
ISBN:	9780438452114

Using Data Mining to Investigate Hospitalization Experiences of Parkinson's Disease Patients.
Al-Shanableh, Najah.

Using Data Mining to Investigate Hospitalization Experiences of Parkinson's Disease Patients. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 167 p.

Source: Dissertations Abstracts International, Volume: 80-05, Section: B.

Thesis (Ph.D.)--New Mexico State University, 2018.

This item must not be added to any third party search indexes.

Parkinson's disease (PD) is a chronic, incurable, and progressive neurological disease that affects approximately 60,000 people each year in the United States. The causes of PD are still uncertain despite the number of studies that have been completed in healthcare. There is a significant gap in what is known about PD, which creates many challenges for treating, and serving PD patients. Additional studies are needed on PD, especially using available healthcare data to develop a better understanding of the hospitalization experience among PD patients. This research aims to understand the factors, which affect the progression of PD, and to identify possible factors associated with readmission, hospitalization's outcome, and determine potential patients' grouping using data mining. The overall purpose of this study is to use a data mining framework to investiand interrelated factors in healthcare data. It is essential to identify what factors are significant to the disease development and the associated risks of PD. Understanding such factors could help in developing a plan to minimize their effect on patients' quality of life. This study utilized hospital discharge dataset for a New Mexico patients between the ages of 30 years and older, who have PD to investigate their hospitalization experience. It also used a Data Mining model as a core method to build information about PD. Several factors were identified for readmission, patients' sub-groups, and hospitalization outcomes. A data mining-based model was presented in this research, for analyzing hospital discharge files for PD insights. Analysis of the patient's data by different data mining techniques indicates that the proposed model could be used for knowledge building, especially a disease-specific knowledge. It is expected this proposed model to open up an entirely new range of healthcare applications. The research findings could help in developing further information about PD and establish the needed base for applying knowledge to data mining techniques in healthcare.

ISBN: 9780438452114Subjects--Topical Terms:

1030799
Information Technology.

Using Data Mining to Investigate Hospitalization Experiences of Parkinson's Disease Patients.
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520 $a Parkinson's disease (PD) is a chronic, incurable, and progressive neurological disease that affects approximately 60,000 people each year in the United States. The causes of PD are still uncertain despite the number of studies that have been completed in healthcare. There is a significant gap in what is known about PD, which creates many challenges for treating, and serving PD patients. Additional studies are needed on PD, especially using available healthcare data to develop a better understanding of the hospitalization experience among PD patients. This research aims to understand the factors, which affect the progression of PD, and to identify possible factors associated with readmission, hospitalization's outcome, and determine potential patients' grouping using data mining. The overall purpose of this study is to use a data mining framework to investiand interrelated factors in healthcare data. It is essential to identify what factors are significant to the disease development and the associated risks of PD. Understanding such factors could help in developing a plan to minimize their effect on patients' quality of life. This study utilized hospital discharge dataset for a New Mexico patients between the ages of 30 years and older, who have PD to investigate their hospitalization experience. It also used a Data Mining model as a core method to build information about PD. Several factors were identified for readmission, patients' sub-groups, and hospitalization outcomes. A data mining-based model was presented in this research, for analyzing hospital discharge files for PD insights. Analysis of the patient's data by different data mining techniques indicates that the proposed model could be used for knowledge building, especially a disease-specific knowledge. It is expected this proposed model to open up an entirely new range of healthcare applications. The research findings could help in developing further information about PD and establish the needed base for applying knowledge to data mining techniques in healthcare.
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