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

Creating domain specific resources f...

Wang, Yan.

FindBook

Google Book

Amazon

博客來

Creating domain specific resources for building semantic role labeling system for operative notes.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Creating domain specific resources for building semantic role labeling system for operative notes./
作者:	Wang, Yan.
面頁冊數:	100 p.
附註:	Source: Dissertation Abstracts International, Volume: 77-03(E), Section: B.
Contained By:	Dissertation Abstracts International77-03B(E).
標題:	Biomedical engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3727808
ISBN:	9781339130323

Creating domain specific resources for building semantic role labeling system for operative notes.
Wang, Yan.

Creating domain specific resources for building semantic role labeling system for operative notes. - 100 p.

Source: Dissertation Abstracts International, Volume: 77-03(E), Section: B.

Thesis (Ph.D.)--University of Minnesota, 2015.

Operative notes contain rich information about techniques, instruments, and materials used in surgeries. With widespread electronic health record (EHR) system adoption throughout healthcare, operative reports are increasingly accessible in electronic format and are potential information sources which may be valuable for a wide variety of secondary functions including new medical knowledge development, decision support, and clinical research. But manual review of large number of reports is time consuming and limits our ability to provide timely evidence-based guide in clinical environment. Automatic extraction of techniques, instruments, materials, and other factors surrounding operative procedures from operative notes can provide an efficient way for physicians to acquire valuable information distilled from diverse experiences reported by clinicians and decide optimal technique approach for patients.

ISBN: 9781339130323Subjects--Topical Terms:

535387
Biomedical engineering.

Creating domain specific resources for building semantic role labeling system for operative notes.
LDR:03144nmm a2200301 4500 001 2069065
005 20160507120512.5
008 170521s2015 ||||||||||||||||| ||eng d
020 $a 9781339130323
035 $a (MiAaPQ)AAI3727808
035 $a AAI3727808
040 $a MiAaPQ $c MiAaPQ
100 1 $a Wang, Yan. $3 1021976
245 1 0 $a Creating domain specific resources for building semantic role labeling system for operative notes.
300 $a 100 p.
500 $a Source: Dissertation Abstracts International, Volume: 77-03(E), Section: B.
500 $a Adviser: Serguei V. Pakhomov.
502 $a Thesis (Ph.D.)--University of Minnesota, 2015.
520 $a Operative notes contain rich information about techniques, instruments, and materials used in surgeries. With widespread electronic health record (EHR) system adoption throughout healthcare, operative reports are increasingly accessible in electronic format and are potential information sources which may be valuable for a wide variety of secondary functions including new medical knowledge development, decision support, and clinical research. But manual review of large number of reports is time consuming and limits our ability to provide timely evidence-based guide in clinical environment. Automatic extraction of techniques, instruments, materials, and other factors surrounding operative procedures from operative notes can provide an efficient way for physicians to acquire valuable information distilled from diverse experiences reported by clinicians and decide optimal technique approach for patients.
520 $a To automate the representation and extraction of the rich information from operative notes, the goal of this research is to create domain specific resources needed for creating a semantic role labeling (SRL) system to extract information from operative notes. The coverage of existing domain-specific resources and general English resources for building a SRL system for operative notes were evaluated on a corpus obtained from the Fairview Health Services and the sublanguage used to describe surgical actions in operative notes was investigated. The results from the study show that general English resources are not adequate for building a SRL system for clinical text. Also the study shows some sublanguage characters of operative notes that can be used for parser adaption. Next, an existing unlexicalized probabilistic context-free grammar (PCFG) parser, the Stanford PCFG parser, was adapted to clinical text for better syntactic parsing performance. Finally, domain specific predicate structure (PAS) frames were created for operative notes, as existing semantic frames for general English are not enough for operative notes. The domain specific resource created in this research can be used to build a SRL system for automatically extracting detailed information from operative notes.
590 $a School code: 0130.
650 4 $a Biomedical engineering. $3 535387
650 4 $a Bioinformatics. $3 553671
650 4 $a Computer science. $3 523869
690 $a 0541
690 $a 0715
690 $a 0984
710 2 $a University of Minnesota. $b Health Informatics. $3 1266007
773 0 $t Dissertation Abstracts International $g 77-03B(E).
790 $a 0130
791 $a Ph.D.
792 $a 2015
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3727808