Published on in Vol 10 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/56342, first published .
Assessing the Ability of a Large Language Model to Score Free-Text Medical Student Clinical Notes: Quantitative Study

Assessing the Ability of a Large Language Model to Score Free-Text Medical Student Clinical Notes: Quantitative Study

Assessing the Ability of a Large Language Model to Score Free-Text Medical Student Clinical Notes: Quantitative Study

Journals

  1. Jamieson A, Holcomb M, Dalton T, Campbell K, Vedovato S, Shakur A, Kang S, Hein D, Lawson J, Danuser G, Scott D. Rubrics to Prompts: Assessing Medical Student Post-Encounter Notes with AI. NEJM AI 2024;1(12) View
  2. Bany Abdelnabi A, Soykan B, Bhatti D, Rabadi G. Usefulness of Large Language Models (LLMs) for Student Feedback on H&P During Clerkship: Artificial Intelligence for Personalized Learning. ACM Transactions on Computing for Healthcare 2025 View
  3. Wei Y, Zhang R, Zhang J, Qi D, Cui W. Research on Intelligent Grading of Physics Problems Based on Large Language Models. Education Sciences 2025;15(2):116 View
  4. Kovari A. AI Gem: Context-Aware Transformer Agents as Digital Twin Tutors for Adaptive Learning. Computers 2025;14(9):367 View
  5. Chen J, Tu H, Chang C, Hsu W, Wang P, Liao C, Chen M. Automated Evaluation of Reflection and Feedback Quality in Workplace-Based Assessments by Using Natural Language Processing: Cross-Sectional Competency-Based Medical Education Study. JMIR Medical Education 2025;11:e81718 View
  6. Mitsuhashi M, Akiba Y, Saitou M, Suzuki K, Ogawa S, Masuno T. AI-Based Assessment of Non-Technical Skills in Prehospital Simulations: A Comparative Validation Study. Healthcare 2025;13(23):3121 View
  7. Takahashi H, Shikino K, Kondo T, Yamada Y, Tomoda Y, Kishi M, Aiyama Y, Nagai S, Enomoto A, Tokushima Y, Shinohara T, Sano F, Matsuura T, Watanabe R, Naito T. AI- vs Human-Based Assessment of Medical Interview Transcripts in a Generative AI–Simulated Patient System: Cross-Sectional Validation Study. JMIR Medical Education 2026;12:e81673 View
  8. Basil M, Ahmed W, Hajeomar R, Strawbridge J, Lynch M, Mukhalalati B. A scoping review of the use of generative artificial intelligence tools in health profession education. BMC Medical Education 2026;26(1) View
  9. Hassanein F, Hussein R, Ahmed Y, El-Guindy J, Ahmed D, Abou-Bakr A. Calibration of AI large language models with human subject matter experts for grading of clinical short-answer responses in dental education. BMC Oral Health 2026;26(1) View
  10. Agarwal P, Agarwal R, Iezhitsa I. AI for Assessment in Medical Education in Post LLM Era: A Scoping Review. Medical Science Educator 2026 View
  11. Guo S, Liu D, Fang X, Meng Y, Zhou Z, Li J, Li M, Luo L, Li H, Cai X, Huang W, Tian X. Current concerns and future directions of large language model ChatGPT in medicine: a machine-learning-driven global-scale bibliometric analysis. International Journal of Surgery 2026;112(2):2805 View
  12. Nolan E, Burke H. Accuracy of large language model transcription of simulated physician-patient verbal interactions. BMC Medical Informatics and Decision Making 2026 View

Books/Policy Documents

  1. Mihara H. Medical Education in the Age of Digital Transformation [Working Title]. View