BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

147 related articles for article (PubMed ID: 38827097)

  • 21. 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]  

  • 22. 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]  

  • 23. An extensive benchmark study on biomedical text generation and mining with ChatGPT.
    Chen Q; Sun H; Liu H; Jiang Y; Ran T; Jin X; Xiao X; Lin Z; Chen H; Niu Z
    Bioinformatics; 2023 Sep; 39(9):. PubMed ID: 37682111
    [TBL] [Abstract][Full Text] [Related]  

  • 24. BioBERT: a pre-trained biomedical language representation model for biomedical text mining.
    Lee J; Yoon W; Kim S; Kim D; Kim S; So CH; Kang J
    Bioinformatics; 2020 Feb; 36(4):1234-1240. PubMed ID: 31501885
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Biomedical Relation Extraction Using Dependency Graph and Decoder-Enhanced Transformer Model.
    Kim S; Yoon J; Kwon O
    Bioengineering (Basel); 2023 May; 10(5):. PubMed ID: 37237656
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Bioformer: an efficient transformer language model for biomedical text mining.
    Fang L; Chen Q; Wei CH; Lu Z; Wang K
    ArXiv; 2023 Feb; ():. PubMed ID: 36945685
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Revisiting Relation Extraction in the era of Large Language Models.
    Wadhwa S; Amir S; Wallace BC
    Proc Conf Assoc Comput Linguist Meet; 2023 Jul; 2023():15566-15589. PubMed ID: 37674787
    [TBL] [Abstract][Full Text] [Related]  

  • 28. A Promising Start and Not a Panacea: ChatGPT's Early Impact and Potential in Medical Science and Biomedical Engineering Research.
    Sohail SS
    Ann Biomed Eng; 2024 May; 52(5):1131-1135. PubMed ID: 37540292
    [TBL] [Abstract][Full Text] [Related]  

  • 29. BioBERT and Similar Approaches for Relation Extraction.
    Bhasuran B
    Methods Mol Biol; 2022; 2496():221-235. PubMed ID: 35713867
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Generative Large Language Models for Detection of Speech Recognition Errors in Radiology Reports.
    Schmidt RA; Seah JCY; Cao K; Lim L; Lim W; Yeung J
    Radiol Artif Intell; 2024 Mar; 6(2):e230205. PubMed ID: 38265301
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Evaluating the OpenAI's GPT-3.5 Turbo's performance in extracting information from scientific articles on diabetic retinopathy.
    Gue CCY; Rahim NDA; Rojas-Carabali W; Agrawal R; Rk P; Abisheganaden J; Yip WF
    Syst Rev; 2024 May; 13(1):135. PubMed ID: 38755704
    [TBL] [Abstract][Full Text] [Related]  

  • 32. BioEGRE: a linguistic topology enhanced method for biomedical relation extraction based on BioELECTRA and graph pointer neural network.
    Zheng X; Wang X; Luo X; Tong F; Zhao D
    BMC Bioinformatics; 2023 Dec; 24(1):486. PubMed ID: 38114906
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Performance of Progressive Generations of GPT on an Exam Designed for Certifying Physicians as Certified Clinical Densitometrists.
    Valdez D; Bunnell A; Lim SY; Sadowski P; Shepherd JA
    J Clin Densitom; 2024; 27(2):101480. PubMed ID: 38401238
    [TBL] [Abstract][Full Text] [Related]  

  • 34. The unreasonable effectiveness of large language models in zero-shot semantic annotation of legal texts.
    Savelka J; Ashley KD
    Front Artif Intell; 2023; 6():1279794. PubMed ID: 38045764
    [TBL] [Abstract][Full Text] [Related]  

  • 35. New meaning for NLP: the trials and tribulations of natural language processing with GPT-3 in ophthalmology.
    Nath S; Marie A; Ellershaw S; Korot E; Keane PA
    Br J Ophthalmol; 2022 Jul; 106(7):889-892. PubMed ID: 35523534
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Leveraging GPT-4 for Identifying Cancer Phenotypes in Electronic Health Records: A Performance Comparison between GPT-4, GPT-3.5-turbo, Flan-T5 and spaCy's Rule-based & Machine Learning-based methods.
    Bhattarai K; Oh IY; Sierra JM; Tang J; Payne PRO; Abrams ZB; Lai AM
    bioRxiv; 2024 Apr; ():. PubMed ID: 37808763
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Generative Pre-trained Transformer 4 makes cardiovascular magnetic resonance reports easy to understand.
    Salam B; Kravchenko D; Nowak S; Sprinkart AM; Weinhold L; Odenthal A; Mesropyan N; Bischoff LM; Attenberger U; Kuetting DL; Luetkens JA; Isaak A
    J Cardiovasc Magn Reson; 2024 Summer; 26(1):101035. PubMed ID: 38460841
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Optimizing Diagnostic Performance of ChatGPT: The Impact of Prompt Engineering on Thoracic Radiology Cases.
    Cesur T; Güneş YC
    Cureus; 2024 May; 16(5):e60009. PubMed ID: 38854352
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Learning to Make Rare and Complex Diagnoses With Generative AI Assistance: Qualitative Study of Popular Large Language Models.
    Abdullahi T; Singh R; Eickhoff C
    JMIR Med Educ; 2024 Feb; 10():e51391. PubMed ID: 38349725
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Utilizing Large Language Models for Enhanced Clinical Trial Matching: A Study on Automation in Patient Screening.
    Beattie J; Neufeld S; Yang D; Chukwuma C; Gul A; Desai N; Jiang S; Dohopolski M
    Cureus; 2024 May; 16(5):e60044. PubMed ID: 38854210
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 8.