BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

124 related articles for article (PubMed ID: 37128373)

  • 1. Extracting Biomedical Factual Knowledge Using Pretrained Language Model and Electronic Health Record Context.
    Yao Z; Cao Y; Yang Z; Deshpande V; Yu H
    AMIA Annu Symp Proc; 2022; 2022():1188-1197. PubMed ID: 37128373
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Context Variance Evaluation of Pretrained Language Models for Prompt-based Biomedical Knowledge Probing.
    Yao Z; Cao Y; Yang Z; Yu H
    AMIA Jt Summits Transl Sci Proc; 2023; 2023():592-601. PubMed ID: 37350903
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. Combining Context and Knowledge Representations for Chemical-Disease Relation Extraction.
    Zhou H; Yang Y; Ning S; Liu Z; Lang C; Lin Y; Huang D
    IEEE/ACM Trans Comput Biol Bioinform; 2019; 16(6):1879-1889. PubMed ID: 29994540
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Chemical-induced disease relation extraction with dependency information and prior knowledge.
    Zhou H; Ning S; Yang Y; Liu Z; Lang C; Lin Y
    J Biomed Inform; 2018 Aug; 84():171-178. PubMed ID: 30017973
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Mining the electronic health record for disease knowledge.
    Chen ES; Sarkar IN
    Methods Mol Biol; 2014; 1159():269-86. PubMed ID: 24788272
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. KEBLM: Knowledge-Enhanced Biomedical Language Models.
    Lai TM; Zhai C; Ji H
    J Biomed Inform; 2023 Jul; 143():104392. PubMed ID: 37211194
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Determining the reasons for medication prescriptions in the EHR using knowledge and natural language processing.
    Li Y; Salmasian H; Harpaz R; Chase H; Friedman C
    AMIA Annu Symp Proc; 2011; 2011():768-76. PubMed ID: 22195134
    [TBL] [Abstract][Full Text] [Related]  

  • 12. CancerBERT: a cancer domain-specific language model for extracting breast cancer phenotypes from electronic health records.
    Zhou S; Wang N; Wang L; Liu H; Zhang R
    J Am Med Inform Assoc; 2022 Jun; 29(7):1208-1216. PubMed ID: 35333345
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. 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]  

  • 15. Unsupervised ensemble ranking of terms in electronic health record notes based on their importance to patients.
    Chen J; Yu H
    J Biomed Inform; 2017 Apr; 68():121-131. PubMed ID: 28267590
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Integration of an OWL-DL knowledge base with an EHR prototype and providing customized information.
    Jing X; Kay S; Marley T; Hardiker NR
    J Med Syst; 2014 Sep; 38(9):75. PubMed ID: 24997857
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Extracting medications and associated adverse drug events using a natural language processing system combining knowledge base and deep learning.
    Chen L; Gu Y; Ji X; Sun Z; Li H; Gao Y; Huang Y
    J Am Med Inform Assoc; 2020 Jan; 27(1):56-64. PubMed ID: 31591641
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A Natural Language Processing System That Links Medical Terms in Electronic Health Record Notes to Lay Definitions: System Development Using Physician Reviews.
    Chen J; Druhl E; Polepalli Ramesh B; Houston TK; Brandt CA; Zulman DM; Vimalananda VG; Malkani S; Yu H
    J Med Internet Res; 2018 Jan; 20(1):e26. PubMed ID: 29358159
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A method for cohort selection of cardiovascular disease records from an electronic health record system.
    Abrahão MTF; Nobre MRC; Gutierrez MA
    Int J Med Inform; 2017 Jun; 102():138-149. PubMed ID: 28495342
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Identifying Goals of Care Conversations in the Electronic Health Record Using Natural Language Processing and Machine Learning.
    Lee RY; Brumback LC; Lober WB; Sibley J; Nielsen EL; Treece PD; Kross EK; Loggers ET; Fausto JA; Lindvall C; Engelberg RA; Curtis JR
    J Pain Symptom Manage; 2021 Jan; 61(1):136-142.e2. PubMed ID: 32858164
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.