These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

93 related articles for article (PubMed ID: 30467557)

  • 1. UArizona at the MADE1.0 NLP Challenge.
    Xu D; Yadav V; Bethard S
    Proc Mach Learn Res; 2018 May; 90():57-65. PubMed ID: 30467557
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Overview of the First Natural Language Processing Challenge for Extracting Medication, Indication, and Adverse Drug Events from Electronic Health Record Notes (MADE 1.0).
    Jagannatha A; Liu F; Liu W; Yu H
    Drug Saf; 2019 Jan; 42(1):99-111. PubMed ID: 30649735
    [TBL] [Abstract][Full Text] [Related]  

  • 3. MADEx: A System for Detecting Medications, Adverse Drug Events, and Their Relations from Clinical Notes.
    Yang X; Bian J; Gong Y; Hogan WR; Wu Y
    Drug Saf; 2019 Jan; 42(1):123-133. PubMed ID: 30600484
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Adverse Drug Event Detection from Electronic Health Records Using Hierarchical Recurrent Neural Networks with Dual-Level Embedding.
    Wunnava S; Qin X; Kakar T; Sen C; Rundensteiner EA; Kong X
    Drug Saf; 2019 Jan; 42(1):113-122. PubMed ID: 30649736
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Extraction of Information Related to Adverse Drug Events from Electronic Health Record Notes: Design of an End-to-End Model Based on Deep Learning.
    Li F; Liu W; Yu H
    JMIR Med Inform; 2018 Nov; 6(4):e12159. PubMed ID: 30478023
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Adverse drug events and medication relation extraction in electronic health records with ensemble deep learning methods.
    Christopoulou F; Tran TT; Sahu SK; Miwa M; Ananiadou S
    J Am Med Inform Assoc; 2020 Jan; 27(1):39-46. PubMed ID: 31390003
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Extraction of Information Related to Drug Safety Surveillance From Electronic Health Record Notes: Joint Modeling of Entities and Relations Using Knowledge-Aware Neural Attentive Models.
    Dandala B; Joopudi V; Tsou CH; Liang JJ; Suryanarayanan P
    JMIR Med Inform; 2020 Jul; 8(7):e18417. PubMed ID: 32459650
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Ensemble method-based extraction of medication and related information from clinical texts.
    Kim Y; Meystre SM
    J Am Med Inform Assoc; 2020 Jan; 27(1):31-38. PubMed ID: 31282932
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Extracting Drug Names and Associated Attributes From Discharge Summaries: Text Mining Study.
    Alfattni G; Belousov M; Peek N; Nenadic G
    JMIR Med Inform; 2021 May; 9(5):e24678. PubMed ID: 33949962
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Detecting Adverse Drug Events with Rapidly Trained Classification Models.
    Chapman AB; Peterson KS; Alba PR; DuVall SL; Patterson OV
    Drug Saf; 2019 Jan; 42(1):147-156. PubMed ID: 30649737
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Temporal indexing of medical entity in Chinese clinical notes.
    Liu Z; Wang X; Chen Q; Tang B; Xu H
    BMC Med Inform Decis Mak; 2019 Jan; 19(Suppl 1):17. PubMed ID: 30700331
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Family History Extraction From Synthetic Clinical Narratives Using Natural Language Processing: Overview and Evaluation of a Challenge Data Set and Solutions for the 2019 National NLP Clinical Challenges (n2c2)/Open Health Natural Language Processing (OHNLP) Competition.
    Shen F; Liu S; Fu S; Wang Y; Henry S; Uzuner O; Liu H
    JMIR Med Inform; 2021 Jan; 9(1):e24008. PubMed ID: 33502329
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Ontology-Based Healthcare Named Entity Recognition from Twitter Messages Using a Recurrent Neural Network Approach.
    Batbaatar E; Ryu KH
    Int J Environ Res Public Health; 2019 Sep; 16(19):. PubMed ID: 31569654
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A multitask bi-directional RNN model for named entity recognition on Chinese electronic medical records.
    Chowdhury S; Dong X; Qian L; Li X; Guan Y; Yang J; Yu Q
    BMC Bioinformatics; 2018 Dec; 19(Suppl 17):499. PubMed ID: 30591015
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A deep learning model incorporating part of speech and self-matching attention for named entity recognition of Chinese electronic medical records.
    Cai X; Dong S; Hu J
    BMC Med Inform Decis Mak; 2019 Apr; 19(Suppl 2):65. PubMed ID: 30961622
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Clinical Named Entity Recognition Using Deep Learning Models.
    Wu Y; Jiang M; Xu J; Zhi D; Xu H
    AMIA Annu Symp Proc; 2017; 2017():1812-1819. PubMed ID: 29854252
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Using the Natural Language Processing System Medical Named Entity Recognition-Japanese to Analyze Pharmaceutical Care Records: Natural Language Processing Analysis.
    Ohno Y; Kato R; Ishikawa H; Nishiyama T; Isawa M; Mochizuki M; Aramaki E; Aomori T
    JMIR Form Res; 2024 Jun; 8():e55798. PubMed ID: 38833694
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Extracting comprehensive clinical information for breast cancer using deep learning methods.
    Zhang X; Zhang Y; Zhang Q; Ren Y; Qiu T; Ma J; Sun Q
    Int J Med Inform; 2019 Dec; 132():103985. PubMed ID: 31627032
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Medical Knowledge Extraction and Analysis from Electronic Medical Records Using Deep Learning.
    Li PL; Yuan ZM; Tu WN; Yu K; Lu DX
    Chin Med Sci J; 2019 Jun; 34(2):133-139. PubMed ID: 31315754
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Combining Contextualized Embeddings and Prior Knowledge for Clinical Named Entity Recognition: Evaluation Study.
    Jiang M; Sanger T; Liu X
    JMIR Med Inform; 2019 Nov; 7(4):e14850. PubMed ID: 31719024
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 5.