514 related articles for article (PubMed ID: 28699564)
1. Detecting clinically relevant new information in clinical notes across specialties and settings.
Zhang R; Pakhomov SVS; Arsoniadis EG; Lee JT; Wang Y; Melton GB
BMC Med Inform Decis Mak; 2017 Jul; 17(Suppl 2):68. PubMed ID: 28699564
[TBL] [Abstract][Full Text] [Related]
2. Using language models to identify relevant new information in inpatient clinical notes.
Zhang R; Pakhomov SV; Lee JT; Melton GB
AMIA Annu Symp Proc; 2014; 2014():1268-76. PubMed ID: 25954438
[TBL] [Abstract][Full Text] [Related]
3. Length and Redundancy of Outpatient Progress Notes Across a Decade at an Academic Medical Center.
Rule A; Bedrick S; Chiang MF; Hribar MR
JAMA Netw Open; 2021 Jul; 4(7):e2115334. PubMed ID: 34279650
[TBL] [Abstract][Full Text] [Related]
4. Contextual Variation of Clinical Notes induced by EHR Migration.
Miller K; Moon S; Fu S; Liu H
AMIA Annu Symp Proc; 2023; 2023():1155-1164. PubMed ID: 38222426
[TBL] [Abstract][Full Text] [Related]
5. Detecting the presence of an indwelling urinary catheter and urinary symptoms in hospitalized patients using natural language processing.
Gundlapalli AV; Divita G; Redd A; Carter ME; Ko D; Rubin M; Samore M; Strymish J; Krein S; Gupta K; Sales A; Trautner BW
J Biomed Inform; 2017 Jul; 71S():S39-S45. PubMed ID: 27404849
[TBL] [Abstract][Full Text] [Related]
6. Estimating redundancy in clinical text.
Searle T; Ibrahim Z; Teo J; Dobson R
J Biomed Inform; 2021 Dec; 124():103938. PubMed ID: 34695581
[TBL] [Abstract][Full Text] [Related]
7. Unsupervised ensemble ranking of terms in electronic health record notes based on their importance to patients.
Chen J; Yu H
J Biomed Inform; 2017 Apr; 68():121-131. PubMed ID: 28267590
[TBL] [Abstract][Full Text] [Related]
8. Automated identification of wound information in clinical notes of patients with heart diseases: Developing and validating a natural language processing application.
Topaz M; Lai K; Dowding D; Lei VJ; Zisberg A; Bowles KH; Zhou L
Int J Nurs Stud; 2016 Dec; 64():25-31. PubMed ID: 27668855
[TBL] [Abstract][Full Text] [Related]
9. Use of "off-the-shelf" information extraction algorithms in clinical informatics: A feasibility study of MetaMap annotation of Italian medical notes.
Chiaramello E; Pinciroli F; Bonalumi A; Caroli A; Tognola G
J Biomed Inform; 2016 Oct; 63():22-32. PubMed ID: 27444186
[TBL] [Abstract][Full Text] [Related]
10. Redundancy in electronic health record corpora: analysis, impact on text mining performance and mitigation strategies.
Cohen R; Elhadad M; Elhadad N
BMC Bioinformatics; 2013 Jan; 14():10. PubMed ID: 23323800
[TBL] [Abstract][Full Text] [Related]
11. Identifying and characterizing highly similar notes in big clinical note datasets.
Gabriel RA; Kuo TT; McAuley J; Hsu CN
J Biomed Inform; 2018 Jun; 82():63-69. PubMed ID: 29679685
[TBL] [Abstract][Full Text] [Related]
12. Identifying Symptom Information in Clinical Notes Using Natural Language Processing.
Koleck TA; Tatonetti NP; Bakken S; Mitha S; Henderson MM; George M; Miaskowski C; Smaldone A; Topaz M
Nurs Res; 2021 May-Jun 01; 70(3):173-183. PubMed ID: 33196504
[TBL] [Abstract][Full Text] [Related]
13. Comparison of 2 Natural Language Processing Methods for Identification of Bleeding Among Critically Ill Patients.
Taggart M; Chapman WW; Steinberg BA; Ruckel S; Pregenzer-Wenzler A; Du Y; Ferraro J; Bucher BT; Lloyd-Jones DM; Rondina MT; Shah RU
JAMA Netw Open; 2018 Oct; 1(6):e183451. PubMed ID: 30646240
[TBL] [Abstract][Full Text] [Related]
14. Finding Important Terms for Patients in Their Electronic Health Records: A Learning-to-Rank Approach Using Expert Annotations.
Chen J; Zheng J; Yu H
JMIR Med Inform; 2016 Nov; 4(4):e40. PubMed ID: 27903489
[TBL] [Abstract][Full Text] [Related]
15. Evaluating measures of redundancy in clinical texts.
Zhang R; Pakhomov S; McInnes BT; Melton GB
AMIA Annu Symp Proc; 2011; 2011():1612-20. PubMed ID: 22195227
[TBL] [Abstract][Full Text] [Related]
16. Scalable relevance ranking algorithm via semantic similarity assessment improves efficiency of medical chart review.
Cai T; He Z; Hong C; Zhang Y; Ho YL; Honerlaw J; Geva A; Ayakulangara Panickan V; King A; Gagnon DR; Gaziano M; Cho K; Liao K; Cai T
J Biomed Inform; 2022 Aug; 132():104109. PubMed ID: 35660521
[TBL] [Abstract][Full Text] [Related]
17. Extracting important information from Chinese Operation Notes with natural language processing methods.
Wang H; Zhang W; Zeng Q; Li Z; Feng K; Liu L
J Biomed Inform; 2014 Apr; 48():130-6. PubMed ID: 24486562
[TBL] [Abstract][Full Text] [Related]
18. A comparative observational study of inpatient clinical note-entry and reading/retrieval styles adopted by physicians.
Rizvi RF; Harder KA; Hultman GM; Adam TJ; Kim M; Pakhomov SV; Melton GB
Int J Med Inform; 2016 Jun; 90():1-11. PubMed ID: 27103191
[TBL] [Abstract][Full Text] [Related]
19. Navigating longitudinal clinical notes with an automated method for detecting new information.
Zhang R; Pakhomov S; Lee JT; Melton GB
Stud Health Technol Inform; 2013; 192():754-8. PubMed ID: 23920658
[TBL] [Abstract][Full Text] [Related]
20. Identifying Diabetes in Clinical Notes in Hebrew: A Novel Text Classification Approach Based on Word Embedding.
Topaz M; Murga L; Grossman C; Daliyot D; Jacobson S; Rozendorn N; Zimlichman E; Furie N
Stud Health Technol Inform; 2019 Aug; 264():393-397. PubMed ID: 31437952
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
