BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

205 related articles for article (PubMed ID: 35333345)

  • 1. 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]  

  • 2. A cross-institutional evaluation on breast cancer phenotyping NLP algorithms on electronic health records.
    Zhou S; Wang N; Wang L; Sun J; Blaes A; Liu H; Zhang R
    Comput Struct Biotechnol J; 2023; 22():32-40. PubMed ID: 37680211
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. A Question-and-Answer System to Extract Data From Free-Text Oncological Pathology Reports (CancerBERT Network): Development Study.
    Mitchell JR; Szepietowski P; Howard R; Reisman P; Jones JD; Lewis P; Fridley BL; Rollison DE
    J Med Internet Res; 2022 Mar; 24(3):e27210. PubMed ID: 35319481
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Extracting clinical named entity for pituitary adenomas from Chinese electronic medical records.
    Fang A; Hu J; Zhao W; Feng M; Fu J; Feng S; Lou P; Ren H; Chen X
    BMC Med Inform Decis Mak; 2022 Mar; 22(1):72. PubMed ID: 35321705
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Transformers for extracting breast cancer information from Spanish clinical narratives.
    Solarte-Pabón O; Montenegro O; García-Barragán A; Torrente M; Provencio M; Menasalvas E; Robles V
    Artif Intell Med; 2023 Sep; 143():102625. PubMed ID: 37673566
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Evaluation of clinical named entity recognition methods for Serbian electronic health records.
    Kaplar A; Stošović M; Kaplar A; Brković V; Naumović R; Kovačević A
    Int J Med Inform; 2022 Aug; 164():104805. PubMed ID: 35653828
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Fine-Tuning Bidirectional Encoder Representations From Transformers (BERT)-Based Models on Large-Scale Electronic Health Record Notes: An Empirical Study.
    Li F; Jin Y; Liu W; Rawat BPS; Cai P; Yu H
    JMIR Med Inform; 2019 Sep; 7(3):e14830. PubMed ID: 31516126
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Identify diabetic retinopathy-related clinical concepts and their attributes using transformer-based natural language processing methods.
    Yu Z; Yang X; Sweeting GL; Ma Y; Stolte SE; Fang R; Wu Y
    BMC Med Inform Decis Mak; 2022 Sep; 22(Suppl 3):255. PubMed ID: 36167551
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Ensembles of natural language processing systems for portable phenotyping solutions.
    Liu C; Ta CN; Rogers JR; Li Z; Lee J; Butler AM; Shang N; Kury FSP; Wang L; Shen F; Liu H; Ena L; Friedman C; Weng C
    J Biomed Inform; 2019 Dec; 100():103318. PubMed ID: 31655273
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. 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]  

  • 13. 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]  

  • 14. Named entity recognition of Chinese electronic medical records based on a hybrid neural network and medical MC-BERT.
    Chen P; Zhang M; Yu X; Li S
    BMC Med Inform Decis Mak; 2022 Dec; 22(1):315. PubMed ID: 36457119
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Automatic Extraction of Comprehensive Drug Safety Information from Adverse Drug Event Narratives in the Korea Adverse Event Reporting System Using Natural Language Processing Techniques.
    Kim S; Kang T; Chung TK; Choi Y; Hong Y; Jung K; Lee H
    Drug Saf; 2023 Aug; 46(8):781-795. PubMed ID: 37330415
    [TBL] [Abstract][Full Text] [Related]  

  • 16. MLM-based typographical error correction of unstructured medical texts for named entity recognition.
    Lee EB; Heo GE; Choi CM; Song M
    BMC Bioinformatics; 2022 Nov; 23(1):486. PubMed ID: 36384464
    [TBL] [Abstract][Full Text] [Related]  

  • 17. exKidneyBERT: a language model for kidney transplant pathology reports and the crucial role of extended vocabularies.
    Yang T; Sucholutsky I; Jen KY; Schonlau M
    PeerJ Comput Sci; 2024; 10():e1888. PubMed ID: 38435545
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Leveraging weak supervision to perform named entity recognition in electronic health records progress notes to identify the ophthalmology exam.
    Wang SY; Huang J; Hwang H; Hu W; Tao S; Hernandez-Boussard T
    Int J Med Inform; 2022 Nov; 167():104864. PubMed ID: 36179600
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A comparative study of pre-trained language models for named entity recognition in clinical trial eligibility criteria from multiple corpora.
    Li J; Wei Q; Ghiasvand O; Chen M; Lobanov V; Weng C; Xu H
    BMC Med Inform Decis Mak; 2022 Sep; 22(Suppl 3):235. PubMed ID: 36068551
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 11.