Use of Radcube for extraction of finding trends in a large radiology practice
about
Cross-sectional relatedness between sentences in breast radiology reports: development of an SVM classifier and evaluation against annotations of five breast radiologistsMachine learning and radiology.Workshop on using natural language processing applications for enhancing clinical decision making: an executive summary.Automatically pairing measured findings across narrative abdomen CT reports.
P2860
Use of Radcube for extraction of finding trends in a large radiology practice
description
2008 nî lūn-bûn
@nan
2008 թուականի Յունիսին հրատարակուած գիտական յօդուած
@hyw
2008 թվականի հունիսին հրատարակված գիտական հոդված
@hy
2008年の論文
@ja
2008年学术文章
@wuu
2008年学术文章
@zh-cn
2008年学术文章
@zh-hans
2008年学术文章
@zh-my
2008年学术文章
@zh-sg
2008年學術文章
@yue
name
Use of Radcube for extraction of finding trends in a large radiology practice
@ast
Use of Radcube for extraction of finding trends in a large radiology practice
@en
Use of Radcube for extraction of finding trends in a large radiology practice
@nl
type
label
Use of Radcube for extraction of finding trends in a large radiology practice
@ast
Use of Radcube for extraction of finding trends in a large radiology practice
@en
Use of Radcube for extraction of finding trends in a large radiology practice
@nl
prefLabel
Use of Radcube for extraction of finding trends in a large radiology practice
@ast
Use of Radcube for extraction of finding trends in a large radiology practice
@en
Use of Radcube for extraction of finding trends in a large radiology practice
@nl
P2093
P2860
P1476
Use of Radcube for extraction of finding trends in a large radiology practice
@en
P2093
Elkan F Halpern
Keith J Dreyer
Mannudeep K Kalra
Markus Stout
Michael A Blake
Pragya A Dang
Thomas J Schultz
P2860
P2888
P304
P356
10.1007/S10278-008-9128-X
P577
2008-06-10T00:00:00Z
P5875
P6179
1033123334