BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

130 related articles for article (PubMed ID: 36032678)

  • 1. Medical terminology-based computing system: a lightweight post-processing solution for out-of-vocabulary multi-word terms.
    Saeed N; Naveed H
    Front Mol Biosci; 2022; 9():928530. PubMed ID: 36032678
    [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. The quest for better clinical word vectors: Ontology based and lexical vector augmentation versus clinical contextual embeddings.
    Nath N; Lee SH; McDonnell MD; Lee I
    Comput Biol Med; 2021 Jul; 134():104433. PubMed ID: 34004575
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. DeIDNER Model: A Neural Network Named Entity Recognition Model for Use in the De-identification of Clinical Notes.
    Syed M; Sexton K; Greer M; Syed S; VanScoy J; Kawsar F; Olson E; Patel K; Erwin J; Bhattacharyya S; Zozus M; Prior F
    Biomed Eng Syst Technol Int Jt Conf BIOSTEC Revis Sel Pap; 2022 Feb; 5():640-647. PubMed ID: 35386186
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Improved biomedical word embeddings in the transformer era.
    Noh J; Kavuluru R
    J Biomed Inform; 2021 Aug; 120():103867. PubMed ID: 34284119
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Multi-Ontology Refined Embeddings (MORE): A hybrid multi-ontology and corpus-based semantic representation model for biomedical concepts.
    Jiang S; Wu W; Tomita N; Ganoe C; Hassanpour S
    J Biomed Inform; 2020 Nov; 111():103581. PubMed ID: 33010425
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Contextual Word Embedding for Biomedical Knowledge Extraction: a Rapid Review and Case Study.
    Vithanage D; Yu P; Wang L; Deng C
    J Healthc Inform Res; 2024 Mar; 8(1):158-179. PubMed ID: 38273979
    [TBL] [Abstract][Full Text] [Related]  

  • 10. The Impact of Specialized Corpora for Word Embeddings in Natural Langage Understanding.
    Neuraz A; Rance B; Garcelon N; Llanos LC; Burgun A; Rosset S
    Stud Health Technol Inform; 2020 Jun; 270():432-436. PubMed ID: 32570421
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Comparing general and specialized word embeddings for biomedical named entity recognition.
    Ramos-Vargas RE; Román-Godínez I; Torres-Ramos S
    PeerJ Comput Sci; 2021; 7():e384. PubMed ID: 33817030
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A Word Pair Dataset for Semantic Similarity and Relatedness in Korean Medical Vocabulary: Reference Development and Validation.
    Yum Y; Lee JM; Jang MJ; Kim Y; Kim JH; Kim S; Shin U; Song S; Joo HJ
    JMIR Med Inform; 2021 Jun; 9(6):e29667. PubMed ID: 34185005
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Training and intrinsic evaluation of lightweight word embeddings for the clinical domain in Spanish.
    Chiu C; Villena F; Martin K; Núñez F; Besa C; Dunstan J
    Front Artif Intell; 2022; 5():970517. PubMed ID: 36213168
    [TBL] [Abstract][Full Text] [Related]  

  • 14. BioWordVec, improving biomedical word embeddings with subword information and MeSH.
    Zhang Y; Chen Q; Yang Z; Lin H; Lu Z
    Sci Data; 2019 May; 6(1):52. PubMed ID: 31076572
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Fast and scalable neural embedding models for biomedical sentence classification.
    Agibetov A; Blagec K; Xu H; Samwald M
    BMC Bioinformatics; 2018 Dec; 19(1):541. PubMed ID: 30577747
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A Study of Neural Word Embeddings for Named Entity Recognition in Clinical Text.
    Wu Y; Xu J; Jiang M; Zhang Y; Xu H
    AMIA Annu Symp Proc; 2015; 2015():1326-33. PubMed ID: 26958273
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Using word embeddings to expand terminology of dietary supplements on clinical notes.
    Fan Y; Pakhomov S; McEwan R; Zhao W; Lindemann E; Zhang R
    JAMIA Open; 2019 Jul; 2(2):246-253. PubMed ID: 31825016
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Transformers-sklearn: a toolkit for medical language understanding with transformer-based models.
    Yang F; Wang X; Ma H; Li J
    BMC Med Inform Decis Mak; 2021 Jul; 21(Suppl 2):90. PubMed ID: 34330244
    [TBL] [Abstract][Full Text] [Related]  

  • 19. DTranNER: biomedical named entity recognition with deep learning-based label-label transition model.
    Hong SK; Lee JG
    BMC Bioinformatics; 2020 Feb; 21(1):53. PubMed ID: 32046638
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Evaluating Biomedical Word Embeddings for Vocabulary Alignment at Scale in the UMLS Metathesaurus Using Siamese Networks.
    Bajaj G; Nguyen V; Wijesiriwardene T; Yip HY; Javangula V; Parthasarathy S; Sheth A; Bodenreider O
    Proc Conf Assoc Comput Linguist Meet; 2022 May; 2022():82-87. PubMed ID: 36093038
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.