183 related articles for article (PubMed ID: 34297002)
21. Development and evaluation of RapTAT: a machine learning system for concept mapping of phrases from medical narratives.
Gobbel GT; Reeves R; Jayaramaraja S; Giuse D; Speroff T; Brown SH; Elkin PL; Matheny ME
J Biomed Inform; 2014 Apr; 48():54-65. PubMed ID: 24316051
[TBL] [Abstract][Full Text] [Related]
22. Natural language processing of symptoms documented in free-text narratives of electronic health records: a systematic review.
Koleck TA; Dreisbach C; Bourne PE; Bakken S
J Am Med Inform Assoc; 2019 Apr; 26(4):364-379. PubMed ID: 30726935
[TBL] [Abstract][Full Text] [Related]
23. Natural Language Processing-Enabled and Conventional Data Capture Methods for Input to Electronic Health Records: A Comparative Usability Study.
Kaufman DR; Sheehan B; Stetson P; Bhatt AR; Field AI; Patel C; Maisel JM
JMIR Med Inform; 2016 Oct; 4(4):e35. PubMed ID: 27793791
[TBL] [Abstract][Full Text] [Related]
24. Evaluation of an automated knowledge-based textual summarization system for longitudinal clinical data, in the intensive care domain.
Goldstein A; Shahar Y; Orenbuch E; Cohen MJ
Artif Intell Med; 2017 Oct; 82():20-33. PubMed ID: 28958803
[TBL] [Abstract][Full Text] [Related]
25. Knowledge Author: facilitating user-driven, domain content development to support clinical information extraction.
Scuba W; Tharp M; Mowery D; Tseytlin E; Liu Y; Drews FA; Chapman WW
J Biomed Semantics; 2016 Jun; 7(1):42. PubMed ID: 27338146
[TBL] [Abstract][Full Text] [Related]
26. A comparison of word embeddings for the biomedical natural language processing.
Wang Y; Liu S; Afzal N; Rastegar-Mojarad M; Wang L; Shen F; Kingsbury P; Liu H
J Biomed Inform; 2018 Nov; 87():12-20. PubMed ID: 30217670
[TBL] [Abstract][Full Text] [Related]
27. A method for cohort selection of cardiovascular disease records from an electronic health record system.
Abrahão MTF; Nobre MRC; Gutierrez MA
Int J Med Inform; 2017 Jun; 102():138-149. PubMed ID: 28495342
[TBL] [Abstract][Full Text] [Related]
28. Developing a Natural Language Processing tool to identify perinatal self-harm in electronic healthcare records.
Ayre K; Bittar A; Kam J; Verma S; Howard LM; Dutta R
PLoS One; 2021; 16(8):e0253809. PubMed ID: 34347787
[TBL] [Abstract][Full Text] [Related]
29. Evaluation of Natural Language Processing (NLP) systems to annotate drug product labeling with MedDRA terminology.
Ly T; Pamer C; Dang O; Brajovic S; Haider S; Botsis T; Milward D; Winter A; Lu S; Ball R
J Biomed Inform; 2018 Jul; 83():73-86. PubMed ID: 29860093
[TBL] [Abstract][Full Text] [Related]
30. Development and application of a high throughput natural language processing architecture to convert all clinical documents in a clinical data warehouse into standardized medical vocabularies.
Afshar M; Dligach D; Sharma B; Cai X; Boyda J; Birch S; Valdez D; Zelisko S; Joyce C; Modave F; Price R
J Am Med Inform Assoc; 2019 Nov; 26(11):1364-1369. PubMed ID: 31145455
[TBL] [Abstract][Full Text] [Related]
31. The Real-World Experiences of Persons With Multiple Sclerosis During the First COVID-19 Lockdown: Application of Natural Language Processing.
Chiavi D; Haag C; Chan A; Kamm CP; Sieber C; Stanikić M; Rodgers S; Pot C; Kesselring J; Salmen A; Rapold I; Calabrese P; Manjaly ZM; Gobbi C; Zecca C; Walther S; Stegmayer K; Hoepner R; Puhan M; von Wyl V
JMIR Med Inform; 2022 Nov; 10(11):e37945. PubMed ID: 36252126
[TBL] [Abstract][Full Text] [Related]
32. Launching into clinical space with medspaCy: a new clinical text processing toolkit in Python.
Eyre H; Chapman AB; Peterson KS; Shi J; Alba PR; Jones MM; Box TL; DuVall SL; Patterson OV
AMIA Annu Symp Proc; 2021; 2021():438-447. PubMed ID: 35308962
[TBL] [Abstract][Full Text] [Related]
33. Reconstructing the patient's natural history from electronic health records.
Najafabadipour M; Zanin M; Rodríguez-González A; Torrente M; Nuñez García B; Cruz Bermudez JL; Provencio M; Menasalvas E
Artif Intell Med; 2020 May; 105():101860. PubMed ID: 32505419
[TBL] [Abstract][Full Text] [Related]
34. Natural Language Processing in Radiology: A Systematic Review.
Pons E; Braun LM; Hunink MG; Kors JA
Radiology; 2016 May; 279(2):329-43. PubMed ID: 27089187
[TBL] [Abstract][Full Text] [Related]
35. Using natural language processing to extract mammographic findings.
Gao H; Aiello Bowles EJ; Carrell D; Buist DS
J Biomed Inform; 2015 Apr; 54():77-84. PubMed ID: 25661260
[TBL] [Abstract][Full Text] [Related]
36. Natural language processing with deep learning for medical adverse event detection from free-text medical narratives: A case study of detecting total hip replacement dislocation.
Borjali A; Magnéli M; Shin D; Malchau H; Muratoglu OK; Varadarajan KM
Comput Biol Med; 2021 Feb; 129():104140. PubMed ID: 33278631
[TBL] [Abstract][Full Text] [Related]
37. Development and Validation of a Natural Language Processing Tool to Generate the CONSORT Reporting Checklist for Randomized Clinical Trials.
Wang F; Schilsky RL; Page D; Califf RM; Cheung K; Wang X; Pang H
JAMA Netw Open; 2020 Oct; 3(10):e2014661. PubMed ID: 33030549
[TBL] [Abstract][Full Text] [Related]
38. Annotating Temporal Relations to Determine the Onset of Psychosis Symptoms.
Viani N; Kam J; Yin L; Verma S; Stewart R; Patel R; Velupillai S
Stud Health Technol Inform; 2019 Aug; 264():418-422. PubMed ID: 31437957
[TBL] [Abstract][Full Text] [Related]
39. Detecting Evidence of Intra-abdominal Surgical Site Infections from Radiology Reports Using Natural Language Processing.
Chapman AB; Mowery DL; Swords DS; Chapman WW; Bucher BT
AMIA Annu Symp Proc; 2017; 2017():515-524. PubMed ID: 29854116
[TBL] [Abstract][Full Text] [Related]
40. 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]
[Previous] [Next] [New Search]
