C. Preiksaitis

Health Informatics · 2023

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom C. Preiksaitis trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Eric J. Topol
  2. Gunther Eysenbach
  3. Sun Huh
  4. Hyunsu Lee
  5. John P. A. Ioannidis
  6. H. Alkaissi
  7. Jeffrey T. Hancock

Papers from C. Preiksaitis's perspective

Ordered by how strongly the researchers C. Preiksaitis trusts endorse each paper. Same corpus, a different order for every researcher.

  1. How Does ChatGPT Perform on the United States Medical Licensing Examination (USMLE)? The Implications of Large Language Models for Medical Education and Knowledge Assessment (JMIR Medical Education)
  2. ChatGPT - Reshaping medical education and clinical management (Pakistan Journal of Medical Sciences)
  3. Are ChatGPT’s knowledge and interpretation ability comparable to those of medical students in Korea for taking a parasitology examination?: a descriptive study (Journal of Educational Evaluation for Health Professions)
  4. The rise of ChatGPT: Exploring its potential in medical education (Anatomical Sciences Education)
  5. Artificial Hallucinations in ChatGPT: Implications in Scientific Writing (Cureus)
  6. The Role of ChatGPT, Generative Language Models, and Artificial Intelligence in Medical Education: A Conversation With ChatGPT and a Call for Papers (JMIR Medical Education)
  7. ChatGPT listed as author on research papers: many scientists disapprove
  8. Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models (medRxiv)
  9. Why Most Published Research Findings Are False
  10. High-performance medicine: the convergence of human and artificial intelligence

Their papers