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

Adverse medical event reduction tech...

Rideout, Karen.

Linked to FindBook

Google Book

Amazon

博客來

Adverse medical event reduction technologies: Identification of primary risk factors of adverse medical events using artificial neural networks.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Adverse medical event reduction technologies: Identification of primary risk factors of adverse medical events using artificial neural networks./
Author:	Rideout, Karen.
Description:	122 p.
Notes:	Source: Masters Abstracts International, Volume: 45-01, page: 0468.
Contained By:	Masters Abstracts International45-01.
Subject:	Engineering, Biomedical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR16466
ISBN:	9780494164662

Adverse medical event reduction technologies: Identification of primary risk factors of adverse medical events using artificial neural networks.
Rideout, Karen.

Adverse medical event reduction technologies: Identification of primary risk factors of adverse medical events using artificial neural networks. - 122 p.

Source: Masters Abstracts International, Volume: 45-01, page: 0468.

Thesis (M.A.Sc.)--Carleton University (Canada), 2006.

This thesis presents research into the area of adverse medical events and their resultant medical errors. Key terminology associated with adverse medical events is clarified and five specific categories of adverse medical events are identified. Information technologies that can be very beneficial in the reduction of adverse medical events are discussed and their importance in the healthcare delivery field is emphasised.

ISBN: 9780494164662Subjects--Topical Terms:

1017684
Engineering, Biomedical.

Adverse medical event reduction technologies: Identification of primary risk factors of adverse medical events using artificial neural networks.
LDR:02391nmm 2200289 4500 001 1834534
005 20071119145715.5
008 130610s2006 eng d
020 $a 9780494164662
035 $a (UMI)AAIMR16466
035 $a AAIMR16466
040 $a UMI $c UMI
100 1 $a Rideout, Karen. $3 1923176
245 1 0 $a Adverse medical event reduction technologies: Identification of primary risk factors of adverse medical events using artificial neural networks.
300 $a 122 p.
500 $a Source: Masters Abstracts International, Volume: 45-01, page: 0468.
502 $a Thesis (M.A.Sc.)--Carleton University (Canada), 2006.
520 $a This thesis presents research into the area of adverse medical events and their resultant medical errors. Key terminology associated with adverse medical events is clarified and five specific categories of adverse medical events are identified. Information technologies that can be very beneficial in the reduction of adverse medical events are discussed and their importance in the healthcare delivery field is emphasised.
520 $a Utilising the United States Food and Drug Association's Adverse Event Reporting System database from the first two quarters of 2004 and artificial neural networks, a neural network with optimal performance was determined and the resultant weights were used to calculate the relative importance of the inputs into the ANN. The optimal ANN was a three-layer feed-forward back-propagation structure using the hyperbolic tangent transfer function.
520 $a An expanded model was prepared to capture a larger set of input variables that may be more highly linked to the occurrence of adverse medication events. The recommended model contains seventeen additional input parameters. A recommended model was also prepared for similar databases in the other areas of adverse medical events in the healthcare field based on the adverse medical event risk factors identified in this work. The FDA AERS is a mandatory reporting system. Recommendation from this work is to utilise this expanded model to establish a mandatory adverse medication event reporting system in Canada.
590 $a School code: 0040.
650 4 $a Engineering, Biomedical. $3 1017684
650 4 $a Engineering, System Science. $3 1018128
650 4 $a Artificial Intelligence. $3 769149
690 $a 0541
690 $a 0790
690 $a 0800
710 2 0 $a Carleton University (Canada). $3 1018407
773 0 $t Masters Abstracts International $g 45-01.
790 $a 0040
791 $a M.A.Sc.
792 $a 2006
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR16466