This paper is in the following e-collection/theme issue:

Foundations of AI (57) Generative Language Models Including ChatGPT (670) Research Methodology - AI (33) Artificial Intelligence (2064)

Published on in Vol 3 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/52095, first published .
Sample Size Considerations for Fine-Tuning Large Language Models for Named Entity Recognition Tasks: Methodological Study

Sample Size Considerations for Fine-Tuning Large Language Models for Named Entity Recognition Tasks: Methodological Study

Sample Size Considerations for Fine-Tuning Large Language Models for Named Entity Recognition Tasks: Methodological Study

Authors of this article:

Zoltan P Majdik1 Author Orcid Image ;   S Scott Graham2 Author Orcid Image ;   Jade C Shiva Edward2 Author Orcid Image ;   Sabrina N Rodriguez3 Author Orcid Image ;   Martha S Karnes4 Author Orcid Image ;   Jared T Jensen2 Author Orcid Image ;   Joshua B Barbour5 Author Orcid Image ;   Justin F Rousseau6, 7 Author Orcid Image
Article Authors Cited by (12) Tweetations (6) Metrics

Journals

  1. Shobayo O, Sasikumar S, Makkar S, Okoyeigbo O. Customer Sentiments in Product Reviews: A Comparative Study with GooglePaLM. Analytics 2024;3(2):241 View
  2. Majdik Z, Graham S. Rhetoric of/with AI: An Introduction. Rhetoric Society Quarterly 2024;54(3):222 View
  3. Zhao J, Long Y, Li S, Li X, Zhang Y, Hu J, Han L, Ren L. Use of artificial intelligence algorithms to analyse systemic sclerosis-interstitial lung disease imaging features. Rheumatology International 2024;44(10):2027 View
  4. Mu X, Huang Z, Chen Q, Shi B, Xu L, Xu Y, Zhang K. DeepEnhancerPPO: An Interpretable Deep Learning Approach for Enhancer Classification. International Journal of Molecular Sciences 2024;25(23):12942 View
  5. Pinard C, Poon A, Lagree A, Wu K, Li J, Tran W. Precision in Parsing: Evaluation of an Open‐Source Named Entity Recognizer (NER) in Veterinary Oncology. Veterinary and Comparative Oncology 2025;23(1):102 View
  6. Long K, Itchuaqiyaq C, Lindgren C, Ogier A, Boyd L, Itchuaqiyaq D, Yunes E. Reimagining Archives in the Age of Automation: A Decolonial and Relational Approach. Technical Communication Quarterly 2025;34(3):336 View
  7. R. A, V. V, Srinivas N, A. A. An integrated IDS for the Internet of Vehicles using a Large Language Model framework. Internet of Things 2025;33:101666 View
  8. Zaunegger J, Singerman P, Narayanan R, Rangaswamy M. RadarTD: A Radar Text Dataset for multi-parameter optimization. Natural Language Processing Journal 2025;12:100178 View
  9. Hasnain M, Aurangzeb K, Alhussein M, Ghani I, Mahmood M. AI in conjunctivitis research: assessing ChatGPT and DeepSeek for etiology, intervention, and citation integrity via hallucination rate analysis. Frontiers in Artificial Intelligence 2025;8 View
  10. Park J, Sim W, Yu J, Park Y, Lee Y. Evaluation of Context-Aware Prompting Techniques for Classification of Tumor Response Categories in Radiology Reports Using Large Language Model. Journal of Imaging Informatics in Medicine 2025 View
  11. Lee S, Kim R. Hypothesis generation from pragmatic causal relationships for latent knowledge reasoning in the civil engineering domain. Computer-Aided Civil and Infrastructure Engineering 2025 View
  12. Hanny D, Schmidt S, Gandhi S, Granitzer M, Resch B. A multimodal GeoAI approach to combining text with spatiotemporal features for enhanced relevance classification of social media posts in disaster response. Big Earth Data 2025:1 View