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 *

199 related articles for article (PubMed ID: 36650800)

  • 21. A novel deep learning approach to extract Chinese clinical entities for lung cancer screening and staging.
    Zhang H; Hu D; Duan H; Li S; Wu N; Lu X
    BMC Med Inform Decis Mak; 2021 Jul; 21(Suppl 2):214. PubMed ID: 34330277
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Adversarial active learning for the identification of medical concepts and annotation inconsistency.
    Yu G; Yang Y; Wang X; Zhen H; He G; Li Z; Zhao Y; Shu Q; Shu L
    J Biomed Inform; 2020 Aug; 108():103481. PubMed ID: 32687985
    [TBL] [Abstract][Full Text] [Related]  

  • 23. 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]  

  • 24. Multi-Label Classification in Patient-Doctor Dialogues With the RoBERTa-WWM-ext + CNN (Robustly Optimized Bidirectional Encoder Representations From Transformers Pretraining Approach With Whole Word Masking Extended Combining a Convolutional Neural Network) Model: Named Entity Study.
    Sun Y; Gao D; Shen X; Li M; Nan J; Zhang W
    JMIR Med Inform; 2022 Apr; 10(4):e35606. PubMed ID: 35451969
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Clinical Named Entity Recognition from Chinese Electronic Medical Records Based on Deep Learning Pretraining.
    Gong L; Zhang Z; Chen S
    J Healthc Eng; 2020; 2020():8829219. PubMed ID: 33299537
    [TBL] [Abstract][Full Text] [Related]  

  • 26. 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]  

  • 27. Chinese medical entity recognition based on the dual-branch TENER model.
    Peng H; Zhang Z; Liu D; Qin X
    BMC Med Inform Decis Mak; 2023 Jul; 23(1):136. PubMed ID: 37488521
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Investigating the Impact of Prompt Engineering on the Performance of Large Language Models for Standardizing Obstetric Diagnosis Text: Comparative Study.
    Wang L; Bi W; Zhao S; Ma Y; Lv L; Meng C; Fu J; Lv H
    JMIR Form Res; 2024 Feb; 8():e53216. PubMed ID: 38329787
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Shapley Idioms: Analysing BERT Sentence Embeddings for General Idiom Token Identification.
    Nedumpozhimana V; Klubička F; Kelleher JD
    Front Artif Intell; 2022; 5():813967. PubMed ID: 35360661
    [TBL] [Abstract][Full Text] [Related]  

  • 30. A pre-trained BERT for Korean medical natural language processing.
    Kim Y; Kim JH; Lee JM; Jang MJ; Yum YJ; Kim S; Shin U; Kim YM; Joo HJ; Song S
    Sci Rep; 2022 Aug; 12(1):13847. PubMed ID: 35974113
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Linking entities through an ontology using word embeddings and syntactic re-ranking.
    Karadeniz İ; Özgür A
    BMC Bioinformatics; 2019 Mar; 20(1):156. PubMed ID: 30917789
    [TBL] [Abstract][Full Text] [Related]  

  • 32. A multi-layer soft lattice based model for Chinese clinical named entity recognition.
    Guo S; Yang W; Han L; Song X; Wang G
    BMC Med Inform Decis Mak; 2022 Jul; 22(1):201. PubMed ID: 35908055
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Chinese clinical named entity recognition with variant neural structures based on BERT methods.
    Li X; Zhang H; Zhou XH
    J Biomed Inform; 2020 Jul; 107():103422. PubMed ID: 32353595
    [TBL] [Abstract][Full Text] [Related]  

  • 34. 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]  

  • 35. Model-based clinical note entity recognition for rheumatoid arthritis using bidirectional encoder representation from transformers.
    Li M; Liu F; Zhu J; Zhang R; Qin Y; Gao D
    Quant Imaging Med Surg; 2022 Jan; 12(1):184-195. PubMed ID: 34993070
    [TBL] [Abstract][Full Text] [Related]  

  • 36. The 2019 n2c2/OHNLP Track on Clinical Semantic Textual Similarity: Overview.
    Wang Y; Fu S; Shen F; Henry S; Uzuner O; Liu H
    JMIR Med Inform; 2020 Nov; 8(11):e23375. PubMed ID: 33245291
    [TBL] [Abstract][Full Text] [Related]  

  • 37. UMLS-based data augmentation for natural language processing of clinical research literature.
    Kang T; Perotte A; Tang Y; Ta C; Weng C
    J Am Med Inform Assoc; 2021 Mar; 28(4):812-823. PubMed ID: 33367705
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Semantic-enhanced graph neural network for named entity recognition in ancient Chinese books.
    Xu Y; Mao C; Wang Z; Jin G; Zhong L; Qian T
    Sci Rep; 2024 Jul; 14(1):17488. PubMed ID: 39080339
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Clinical concept normalization with a hybrid natural language processing system combining multilevel matching and machine learning ranking.
    Chen L; Fu W; Gu Y; Sun Z; Li H; Li E; Jiang L; Gao Y; Huang Y
    J Am Med Inform Assoc; 2020 Oct; 27(10):1576-1584. PubMed ID: 33029642
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Integration of natural and deep artificial cognitive models in medical images: BERT-based NER and relation extraction for electronic medical records.
    Guo B; Liu H; Niu L
    Front Neurosci; 2023; 17():1266771. PubMed ID: 37732304
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 10.