209 related articles for article (PubMed ID: 37833661)
1. Negation recognition in clinical natural language processing using a combination of the NegEx algorithm and a convolutional neural network.
Argüello-González G; Aquino-Esperanza J; Salvador D; Bretón-Romero R; Del Río-Bermudez C; Tello J; Menke S
BMC Med Inform Decis Mak; 2023 Oct; 23(1):216. PubMed ID: 37833661
[TBL] [Abstract][Full Text] [Related]
2. DEEPEN: A negation detection system for clinical text incorporating dependency relation into NegEx.
Mehrabi S; Krishnan A; Sohn S; Roch AM; Schmidt H; Kesterson J; Beesley C; Dexter P; Max Schmidt C; Liu H; Palakal M
J Biomed Inform; 2015 Apr; 54():213-9. PubMed ID: 25791500
[TBL] [Abstract][Full Text] [Related]
3. Comparing natural language processing tools to extract medical problems from narrative text.
Meystre SM; Haug PJ
AMIA Annu Symp Proc; 2005; 2005():525-9. PubMed ID: 16779095
[TBL] [Abstract][Full Text] [Related]
4. Biomedical negation scope detection with conditional random fields.
Agarwal S; Yu H
J Am Med Inform Assoc; 2010; 17(6):696-701. PubMed ID: 20962133
[TBL] [Abstract][Full Text] [Related]
5. An efficient pancreatic cyst identification methodology using natural language processing.
Mehrabi S; Schmidt CM; Waters JA; Beesley C; Krishnan A; Kesterson J; Dexter P; Al-Haddad MA; Tierney WM; Palakal M
Stud Health Technol Inform; 2013; 192():822-6. PubMed ID: 23920672
[TBL] [Abstract][Full Text] [Related]
6. Negation and uncertainty detection in clinical texts written in Spanish: a deep learning-based approach.
Solarte Pabón O; Montenegro O; Torrente M; Rodríguez González A; Provencio M; Menasalvas E
PeerJ Comput Sci; 2022; 8():e913. PubMed ID: 35494817
[TBL] [Abstract][Full Text] [Related]
7. Identification of patients' smoking status using an explainable AI approach: a Danish electronic health records case study.
Ebrahimi A; Henriksen MBH; Brasen CL; Hilberg O; Hansen TF; Jensen LH; Peimankar A; Wiil UK
BMC Med Res Methodol; 2024 May; 24(1):114. PubMed ID: 38760718
[TBL] [Abstract][Full Text] [Related]
8. Implementation and evaluation of a negation tagger in a pipeline-based system for information extract from pathology reports.
Mitchell KJ; Becich MJ; Berman JJ; Chapman WW; Gilbertson J; Gupta D; Harrison J; Legowski E; Crowley RS
Stud Health Technol Inform; 2004; 107(Pt 1):663-7. PubMed ID: 15360896
[TBL] [Abstract][Full Text] [Related]
9. A clinical text classification paradigm using weak supervision and deep representation.
Wang Y; Sohn S; Liu S; Shen F; Wang L; Atkinson EJ; Amin S; Liu H
BMC Med Inform Decis Mak; 2019 Jan; 19(1):1. PubMed ID: 30616584
[TBL] [Abstract][Full Text] [Related]
10. French FastContext: A publicly accessible system for detecting negation, temporality and experiencer in French clinical notes.
Mirzapour M; Abdaoui A; Tchechmedjiev A; Digan W; Bringay S; Jonquet C
J Biomed Inform; 2021 May; 117():103733. PubMed ID: 33737205
[TBL] [Abstract][Full Text] [Related]
11. Task definition, annotated dataset, and supervised natural language processing models for symptom extraction from unstructured clinical notes.
Steinkamp JM; Bala W; Sharma A; Kantrowitz JJ
J Biomed Inform; 2020 Feb; 102():103354. PubMed ID: 31838210
[TBL] [Abstract][Full Text] [Related]
12. Facilitating clinical research through automation: Combining optical character recognition with natural language processing.
Hom J; Nikowitz J; Ottesen R; Niland JC
Clin Trials; 2022 Oct; 19(5):504-511. PubMed ID: 35608136
[TBL] [Abstract][Full Text] [Related]
13. Negation detection in Dutch clinical texts: an evaluation of rule-based and machine learning methods.
van Es B; Reteig LC; Tan SC; Schraagen M; Hemker MM; Arends SRS; Rios MAR; Haitjema S
BMC Bioinformatics; 2023 Jan; 24(1):10. PubMed ID: 36624385
[TBL] [Abstract][Full Text] [Related]
14. Does BERT need domain adaptation for clinical negation detection?
Lin C; Bethard S; Dligach D; Sadeque F; Savova G; Miller TA
J Am Med Inform Assoc; 2020 Apr; 27(4):584-591. PubMed ID: 32044989
[TBL] [Abstract][Full Text] [Related]
15. Negation detection in Swedish clinical text: An adaption of NegEx to Swedish.
Skeppstedt M
J Biomed Semantics; 2011; 2 Suppl 3(Suppl 3):S3. PubMed ID: 21992616
[TBL] [Abstract][Full Text] [Related]
16. Classifying social determinants of health from unstructured electronic health records using deep learning-based natural language processing.
Han S; Zhang RF; Shi L; Richie R; Liu H; Tseng A; Quan W; Ryan N; Brent D; Tsui FR
J Biomed Inform; 2022 Mar; 127():103984. PubMed ID: 35007754
[TBL] [Abstract][Full Text] [Related]
17. The Impact of Pretrained Language Models on Negation and Speculation Detection in Cross-Lingual Medical Text: Comparative Study.
Rivera Zavala R; Martinez P
JMIR Med Inform; 2020 Dec; 8(12):e18953. PubMed ID: 33270027
[TBL] [Abstract][Full Text] [Related]
18. Evaluation of clinical named entity recognition methods for Serbian electronic health records.
Kaplar A; Stošović M; Kaplar A; Brković V; Naumović R; Kovačević A
Int J Med Inform; 2022 Aug; 164():104805. PubMed ID: 35653828
[TBL] [Abstract][Full Text] [Related]
19. De-identification of clinical free text using natural language processing: A systematic review of current approaches.
Kovačević A; Bašaragin B; Milošević N; Nenadić G
Artif Intell Med; 2024 May; 151():102845. PubMed ID: 38555848
[TBL] [Abstract][Full Text] [Related]
20. Negation-based transfer learning for improving biomedical Named Entity Recognition and Relation Extraction.
Fabregat H; Duque A; Martinez-Romo J; Araujo L
J Biomed Inform; 2023 Feb; 138():104279. PubMed ID: 36610608
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
