東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Linked to FindBook

Google Book

Amazon

博客來

An Assessment of Spatial and Temporal Similarities for Cases and Deaths in Rare Disease Events: a Case Study of Ebola Virus Disease and Coronavirus Disease 2019.

Record Type:	Electronic resources : Monograph/item
Title/Author:	An Assessment of Spatial and Temporal Similarities for Cases and Deaths in Rare Disease Events: a Case Study of Ebola Virus Disease and Coronavirus Disease 2019./
Author:	Kapoor, Esha.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
Description:	140 p.
Notes:	Source: Masters Abstracts International, Volume: 82-07.
Contained By:	Masters Abstracts International82-07.
Subject:	Information science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28261128
ISBN:	9798557070317

An Assessment of Spatial and Temporal Similarities for Cases and Deaths in Rare Disease Events: a Case Study of Ebola Virus Disease and Coronavirus Disease 2019.
Kapoor, Esha.

An Assessment of Spatial and Temporal Similarities for Cases and Deaths in Rare Disease Events: a Case Study of Ebola Virus Disease and Coronavirus Disease 2019. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 140 p.

Source: Masters Abstracts International, Volume: 82-07.

Thesis (M.S.)--University of Massachusetts Boston, 2020.

This item must not be sold to any third party vendors.

This study examines the spatiotemporal characterization of rare disease events such as the Ebola Virus Disease (EVD) outbreak in West Africa and COVID-19 in the United States. To study this, we utilize cluster analysis, an unsupervised learning technique that groups data objects based on similarity. Specifically, this thesis aims to identify patterns in the confirmed cases and deaths associated with EVD and COVID-19 across spatial regions and time periods, respectively. This thesis also studies the role of socio-economic factors in the EVD and COVID-19 outbreak. For this, socio-economics factors related to population, education, and health care for the different spatial regions are taken into consideration. Overall, outcomes from this thesis poses implications in developing strategies and policies for quality controls necessary to manage the spread of rare disease events.

ISBN: 9798557070317Subjects--Topical Terms:

554358
Information science.
Subjects--Index Terms:

Clustering

An Assessment of Spatial and Temporal Similarities for Cases and Deaths in Rare Disease Events: a Case Study of Ebola Virus Disease and Coronavirus Disease 2019.
LDR:02149nmm a2200385 4500 001 2345875
005 20220613064804.5
008 241004s2020 ||||||||||||||||| ||eng d
020 $a 9798557070317
035 $a (MiAaPQ)AAI28261128
035 $a AAI28261128
040 $a MiAaPQ $c MiAaPQ
100 1 $a Kapoor, Esha. $3 3684885
245 1 0 $a An Assessment of Spatial and Temporal Similarities for Cases and Deaths in Rare Disease Events: a Case Study of Ebola Virus Disease and Coronavirus Disease 2019.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2020
300 $a 140 p.
500 $a Source: Masters Abstracts International, Volume: 82-07.
500 $a Advisor: Namayanja, Josephine;Chakraborty, Atreya.
502 $a Thesis (M.S.)--University of Massachusetts Boston, 2020.
506 $a This item must not be sold to any third party vendors.
520 $a This study examines the spatiotemporal characterization of rare disease events such as the Ebola Virus Disease (EVD) outbreak in West Africa and COVID-19 in the United States. To study this, we utilize cluster analysis, an unsupervised learning technique that groups data objects based on similarity. Specifically, this thesis aims to identify patterns in the confirmed cases and deaths associated with EVD and COVID-19 across spatial regions and time periods, respectively. This thesis also studies the role of socio-economic factors in the EVD and COVID-19 outbreak. For this, socio-economics factors related to population, education, and health care for the different spatial regions are taken into consideration. Overall, outcomes from this thesis poses implications in developing strategies and policies for quality controls necessary to manage the spread of rare disease events.
590 $a School code: 1074.
650 4 $a Information science. $3 554358
650 4 $a Public health. $3 534748
650 4 $a Health care management. $3 2122906
650 4 $a COVID-19. $3 3554449
653 $a Clustering
653 $a COVID-19
653 $a Ebola Virus Disease
653 $a K-means
653 $a Rare Disease
653 $a Spatiotemporal
690 $a 0723
690 $a 0573
690 $a 0769
710 2 $a University of Massachusetts Boston. $b Information Technology (MS). $3 3684886
773 0 $t Masters Abstracts International $g 82-07.
790 $a 1074
791 $a M.S.
792 $a 2020
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28261128