Matches in SemOpenAlex for { <https://semopenalex.org/work/W2914936411> ?p ?o ?g. }
- W2914936411 endingPage "378" @default.
- W2914936411 startingPage "357" @default.
- W2914936411 abstract "Electronic health records (EHR) capture “real-world” disease and care processes and hence offer richer and more generalizable data for comparative effectiveness research than traditional randomized clinical trial studies. With the increasingly broadening adoption of EHR worldwide, there is a growing need to widen the use of EHR data to support clinical research. A big barrier to this goal is that much of the information in EHR is still narrative. This chapter describes the foundation of biomedical language processing and explains how traditional machine learning and the state-of-the-art deep learning techniques can be employed in the context of extracting and transforming narrative information in EHR to support clinical research." @default.
- W2914936411 created "2019-02-21" @default.
- W2914936411 creator A5009604048 @default.
- W2914936411 creator A5017601806 @default.
- W2914936411 creator A5047059244 @default.
- W2914936411 date "2019-01-01" @default.
- W2914936411 modified "2023-09-30" @default.
- W2914936411 title "Advancing Clinical Research Through Natural Language Processing on Electronic Health Records: Traditional Machine Learning Meets Deep Learning" @default.
- W2914936411 cites W1152166452 @default.
- W2914936411 cites W1501578663 @default.
- W2914936411 cites W1504212872 @default.
- W2914936411 cites W1554576613 @default.
- W2914936411 cites W1602443498 @default.
- W2914936411 cites W1611282172 @default.
- W2914936411 cites W1676691994 @default.
- W2914936411 cites W1727290854 @default.
- W2914936411 cites W1908709347 @default.
- W2914936411 cites W1977812329 @default.
- W2914936411 cites W1982464493 @default.
- W2914936411 cites W1985417340 @default.
- W2914936411 cites W2005853109 @default.
- W2914936411 cites W2007321142 @default.
- W2914936411 cites W2021677363 @default.
- W2914936411 cites W2036935277 @default.
- W2914936411 cites W2051743300 @default.
- W2914936411 cites W2058397078 @default.
- W2914936411 cites W2071478164 @default.
- W2914936411 cites W2071806619 @default.
- W2914936411 cites W2077026347 @default.
- W2914936411 cites W2087227067 @default.
- W2914936411 cites W2093157872 @default.
- W2914936411 cites W2094122630 @default.
- W2914936411 cites W2094993339 @default.
- W2914936411 cites W2099131015 @default.
- W2914936411 cites W2099307202 @default.
- W2914936411 cites W2099866409 @default.
- W2914936411 cites W2100216539 @default.
- W2914936411 cites W2102794349 @default.
- W2914936411 cites W2103592462 @default.
- W2914936411 cites W2115915625 @default.
- W2914936411 cites W2117994680 @default.
- W2914936411 cites W2118367849 @default.
- W2914936411 cites W2121740558 @default.
- W2914936411 cites W2125726375 @default.
- W2914936411 cites W2128681611 @default.
- W2914936411 cites W2128718068 @default.
- W2914936411 cites W2131866978 @default.
- W2914936411 cites W2133312387 @default.
- W2914936411 cites W2135187880 @default.
- W2914936411 cites W2136922672 @default.
- W2914936411 cites W2140943358 @default.
- W2914936411 cites W2141756401 @default.
- W2914936411 cites W2153985884 @default.
- W2914936411 cites W2156909104 @default.
- W2914936411 cites W2157331557 @default.
- W2914936411 cites W2159636537 @default.
- W2914936411 cites W2160053034 @default.
- W2914936411 cites W2160194473 @default.
- W2914936411 cites W2165067209 @default.
- W2914936411 cites W2165336645 @default.
- W2914936411 cites W2165470797 @default.
- W2914936411 cites W2166735184 @default.
- W2914936411 cites W2167414941 @default.
- W2914936411 cites W2168811230 @default.
- W2914936411 cites W2169918010 @default.
- W2914936411 cites W2192572088 @default.
- W2914936411 cites W2284851926 @default.
- W2914936411 cites W2290827644 @default.
- W2914936411 cites W2404901863 @default.
- W2914936411 cites W2488984245 @default.
- W2914936411 cites W2513652809 @default.
- W2914936411 cites W2611370172 @default.
- W2914936411 cites W2768488789 @default.
- W2914936411 cites W2802736684 @default.
- W2914936411 cites W2963967185 @default.
- W2914936411 cites W4205947740 @default.
- W2914936411 cites W4230722969 @default.
- W2914936411 cites W4230900352 @default.
- W2914936411 cites W4237515741 @default.
- W2914936411 cites W4244340606 @default.
- W2914936411 cites W4246774901 @default.
- W2914936411 cites W95851278 @default.
- W2914936411 cites W2098332568 @default.
- W2914936411 doi "https://doi.org/10.1007/978-3-319-98779-8_17" @default.
- W2914936411 hasPublicationYear "2019" @default.
- W2914936411 type Work @default.
- W2914936411 sameAs 2914936411 @default.
- W2914936411 citedByCount "9" @default.
- W2914936411 countsByYear W29149364112019 @default.
- W2914936411 countsByYear W29149364112020 @default.
- W2914936411 countsByYear W29149364112021 @default.
- W2914936411 countsByYear W29149364112022 @default.
- W2914936411 countsByYear W29149364112023 @default.
- W2914936411 crossrefType "book-chapter" @default.
- W2914936411 hasAuthorship W2914936411A5009604048 @default.
- W2914936411 hasAuthorship W2914936411A5017601806 @default.
- W2914936411 hasAuthorship W2914936411A5047059244 @default.
- W2914936411 hasConcept C108583219 @default.