東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Similarity Measures for Medical Even...

Fredrickson, Joel Scott.

FindBook

Google Book

Amazon

博客來

Similarity Measures for Medical Event Sequences: Prospects for Clinical Decision-Making.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Similarity Measures for Medical Event Sequences: Prospects for Clinical Decision-Making./
作者:	Fredrickson, Joel Scott.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:	153 p.
附註:	Source: Dissertations Abstracts International, Volume: 80-11, Section: B.
Contained By:	Dissertations Abstracts International80-11B.
標題:	Health sciences. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13812100
ISBN:	9781392146316

Similarity Measures for Medical Event Sequences: Prospects for Clinical Decision-Making.
Fredrickson, Joel Scott.

Similarity Measures for Medical Event Sequences: Prospects for Clinical Decision-Making. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 153 p.

Source: Dissertations Abstracts International, Volume: 80-11, Section: B.

Thesis (Ph.D.)--University of Colorado at Denver, 2019.

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

This dissertation advances the use of a scientific artifact to assist with clinical decision-making. Specifically, we develop and evaluate a similarity measure (OTCS-MES) adapted to medical event sequences (MESs). We further evaluate the decision-making performance of OTCS-MES as an extended clinical decision support tool for new health care domains. To expand the application of OTCS-MES, we generalize its application to improve efficacy for medical event sequences recorded in domains other than the inpatient setting for which it was first developed. Assessment uses industry recognized "gold standards" in place to benchmark health care facility performance. Assessing the generalized measure's performance requires experimentation on the newly extended OTCS-MES, along with more classical inferential methods integrating data elements inherent to MESs. This dissertation begins with a literature review that broadly describes the many inhibitors to physician adoption of technology. It explains how many of these inhibitors are unique to health care. The literature review concludes with a narrower focus on the lack of effective clinical decision support tools available to providers and provision of a similarity measure using medical event sequences. After the literature review, the empirical studies develop and evaluate our MES similarity measure; a decision support tool unique and beneficial to health care. These studies address the proposition that a MES adapted similarity measure performs differently and ultimately better within the health care context.

ISBN: 9781392146316Subjects--Topical Terms:

3168359
Health sciences.

Similarity Measures for Medical Event Sequences: Prospects for Clinical Decision-Making.
LDR:02688nmm a2200337 4500 001 2208828
005 20191025102424.5
008 201008s2019 ||||||||||||||||| ||eng d
020 $a 9781392146316
035 $a (MiAaPQ)AAI13812100
035 $a (MiAaPQ)ucdenver:11185
035 $a AAI13812100
040 $a MiAaPQ $c MiAaPQ
100 1 $a Fredrickson, Joel Scott. $3 3435884
245 1 0 $a Similarity Measures for Medical Event Sequences: Prospects for Clinical Decision-Making.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2019
300 $a 153 p.
500 $a Source: Dissertations Abstracts International, Volume: 80-11, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Mannino, Michael.
502 $a Thesis (Ph.D.)--University of Colorado at Denver, 2019.
506 $a This item must not be sold to any third party vendors.
520 $a This dissertation advances the use of a scientific artifact to assist with clinical decision-making. Specifically, we develop and evaluate a similarity measure (OTCS-MES) adapted to medical event sequences (MESs). We further evaluate the decision-making performance of OTCS-MES as an extended clinical decision support tool for new health care domains. To expand the application of OTCS-MES, we generalize its application to improve efficacy for medical event sequences recorded in domains other than the inpatient setting for which it was first developed. Assessment uses industry recognized "gold standards" in place to benchmark health care facility performance. Assessing the generalized measure's performance requires experimentation on the newly extended OTCS-MES, along with more classical inferential methods integrating data elements inherent to MESs. This dissertation begins with a literature review that broadly describes the many inhibitors to physician adoption of technology. It explains how many of these inhibitors are unique to health care. The literature review concludes with a narrower focus on the lack of effective clinical decision support tools available to providers and provision of a similarity measure using medical event sequences. After the literature review, the empirical studies develop and evaluate our MES similarity measure; a decision support tool unique and beneficial to health care. These studies address the proposition that a MES adapted similarity measure performs differently and ultimately better within the health care context.
590 $a School code: 0765.
650 4 $a Health sciences. $3 3168359
650 4 $a Information science. $3 554358
650 4 $a Computer science. $3 523869
690 $a 0566
690 $a 0723
690 $a 0984
710 2 $a University of Colorado at Denver. $b Computer Science and Information Systems. $3 2106359
773 0 $t Dissertations Abstracts International $g 80-11B.
790 $a 0765
791 $a Ph.D.
792 $a 2019
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13812100