BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

118 related articles for article (PubMed ID: 33232839)

  • 1. From electronic health records to terminology base: A novel knowledge base enrichment approach.
    Zhang J; Zhang Z; Zhang H; Ma Z; Ye Q; He P; Zhou Y
    J Biomed Inform; 2021 Jan; 113():103628. PubMed ID: 33232839
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Use of word and graph embedding to measure semantic relatedness between Unified Medical Language System concepts.
    Mao Y; Fung KW
    J Am Med Inform Assoc; 2020 Oct; 27(10):1538-1546. PubMed ID: 33029614
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Clinical Assistant Diagnosis for Electronic Medical Record Based on Convolutional Neural Network.
    Yang Z; Huang Y; Jiang Y; Sun Y; Zhang YJ; Luo P
    Sci Rep; 2018 Apr; 8(1):6329. PubMed ID: 29679019
    [TBL] [Abstract][Full Text] [Related]  

  • 5. An attention-based deep learning model for clinical named entity recognition of Chinese electronic medical records.
    Li L; Zhao J; Hou L; Zhai Y; Shi J; Cui F
    BMC Med Inform Decis Mak; 2019 Dec; 19(Suppl 5):235. PubMed ID: 31801540
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Continual knowledge infusion into pre-trained biomedical language models.
    Jha K; Zhang A
    Bioinformatics; 2022 Jan; 38(2):494-502. PubMed ID: 34554186
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Jointly learning word embeddings using a corpus and a knowledge base.
    Alsuhaibani M; Bollegala D; Maehara T; Kawarabayashi KI
    PLoS One; 2018; 13(3):e0193094. PubMed ID: 29529052
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Multiview Incomplete Knowledge Graph Integration with application to cross-institutional EHR data harmonization.
    Zhou D; Gan Z; Shi X; Patwari A; Rush E; Bonzel CL; Panickan VA; Hong C; Ho YL; Cai T; Costa L; Li X; Castro VM; Murphy SN; Brat G; Weber G; Avillach P; Gaziano JM; Cho K; Liao KP; Lu J; Cai T
    J Biomed Inform; 2022 Sep; 133():104147. PubMed ID: 35872266
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A Knowledge Graph Entity Disambiguation Method Based on Entity-Relationship Embedding and Graph Structure Embedding.
    Ma J; Li D; Chen Y; Qiao Y; Zhu H; Zhang X
    Comput Intell Neurosci; 2021; 2021():2878189. PubMed ID: 34603428
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Research on Chinese medical named entity recognition based on collaborative cooperation of multiple neural network models.
    Ji B; Li S; Yu J; Ma J; Tang J; Wu Q; Tan Y; Liu H; Ji Y
    J Biomed Inform; 2020 Apr; 104():103395. PubMed ID: 32109551
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Development of a Knowledge Graph Embeddings Model for Pain.
    Chaturvedi J; Wang T; Velupillai S; Stewart R; Roberts A
    AMIA Annu Symp Proc; 2023; 2023():299-308. PubMed ID: 38222382
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. Improving medical term embeddings using UMLS Metathesaurus.
    Chanda AK; Bai T; Yang Z; Vucetic S
    BMC Med Inform Decis Mak; 2022 Apr; 22(1):114. PubMed ID: 35488252
    [TBL] [Abstract][Full Text] [Related]  

  • 14. An effective knowledge graph entity alignment model based on multiple information.
    Zhu B; Bao T; Han R; Cui H; Han J; Liu L; Peng T
    Neural Netw; 2023 May; 162():83-98. PubMed ID: 36893693
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Named Entity Recognition in Chinese Clinical Text Using Deep Neural Network.
    Wu Y; Jiang M; Lei J; Xu H
    Stud Health Technol Inform; 2015; 216():624-8. PubMed ID: 26262126
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A novel framework for biomedical entity sense induction.
    Lossio-Ventura JA; Bian J; Jonquet C; Roche M; Teisseire M
    J Biomed Inform; 2018 Aug; 84():31-41. PubMed ID: 29935347
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Chinese clinical named entity recognition with radical-level feature and self-attention mechanism.
    Yin M; Mou C; Xiong K; Ren J
    J Biomed Inform; 2019 Oct; 98():103289. PubMed ID: 31541715
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Optimizing Corpus Creation for Training Word Embedding in Low Resource Domains: A Case Study in Autism Spectrum Disorder (ASD).
    Gu Y; Leroy G; Pettygrove S; Galindo MK; Kurzius-Spencer M
    AMIA Annu Symp Proc; 2018; 2018():508-517. PubMed ID: 30815091
    [TBL] [Abstract][Full Text] [Related]  

  • 19. SiBERT: A Siamese-based BERT network for Chinese medical entities alignment.
    Ma Z; Zhao L; Li J; Xu X; Li J
    Methods; 2022 Sep; 205():133-139. PubMed ID: 35798258
    [TBL] [Abstract][Full Text] [Related]  

  • 20. An automatic approach for constructing a knowledge base of symptoms in Chinese.
    Ruan T; Wang M; Sun J; Wang T; Zeng L; Yin Y; Gao J
    J Biomed Semantics; 2017 Sep; 8(Suppl 1):33. PubMed ID: 29297414
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.