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01000naa a22002652 4500 |
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NLM109955625 |
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DE-627 |
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231222s2000 xx ||||| 00| ||eng c |
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|a pubmed24n0367.xml
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|a (DE-627)NLM109955625
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|a (NLM)11080001
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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100 |
1 |
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|a Starren, J
|e verfasserin
|4 aut
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1 |
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|a When seconds are counted
|b tools for mobile, high-resolution time-motion studies
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|c 2000
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|a Text
|b txt
|2 rdacontent
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|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
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|a Band
|b nc
|2 rdacarrier
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500 |
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|a Date Completed 08.03.2001
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|a Date Revised 13.11.2018
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|a published: Print
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|a Citation Status MEDLINE
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|a Time-motion (TM) studies are often considered the gold-standard for measurements of the impact of computer systems on task flow and duration. However, in many clinical environments tasks occur too rapidly and have too short of a duration to be captured with conventional paper-based TM methods. Observers may also with to categorize caregiver activities along multiple axes simultaneously. This multi-axial characteristic of clinical activity has been modeled as multiple, parallel finite-state sets and implemented in three computerized data collection tools. Radiology reporting is a domain in which tasks can be characterized by multiple attributes. A radiologist may also switch among multiple tasks in a single minute. The use of these tools to measure the impact of an Automated Speech Recognition (ASR) system on Radiology reporting is presented
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|a Comparative Study
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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700 |
1 |
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|a Chan, S
|e verfasserin
|4 aut
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700 |
1 |
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|a Tahil, F
|e verfasserin
|4 aut
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700 |
1 |
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|a White, T
|e verfasserin
|4 aut
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773 |
0 |
8 |
|i Enthalten in
|t Proceedings. AMIA Symposium
|d 1998
|g (2000) vom: 01., Seite 833-7
|w (DE-627)NLM098642928
|x 1531-605X
|7 nnns
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|g year:2000
|g day:01
|g pages:833-7
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|a GBV_ILN_350
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951 |
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|a AR
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952 |
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|j 2000
|b 01
|h 833-7
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