articleBMC Medical EducationFeb 14, 2024GOLD OA

Performance of ChatGPT on Chinese national medical licensing examinations: a five-year examination evaluation study for physicians, pharmacists and nurses

Sichuan University · West China Hospital of Sichuan University

PubMed
Indexed incrossrefdoajpubmed

Abstract

Background

Large language models like ChatGPT have revolutionized the field of natural language processing with their capability to comprehend and generate textual content, showing great potential to play a role in medical education. This study aimed to quantitatively evaluate and comprehensively analysis the performance of ChatGPT on three types of national medical examinations in China, including National Medical Licensing Examination (NMLE), National Pharmacist Licensing Examination (NPLE), and National Nurse Licensing Examination (NNLE).

Methods

We collected questions from Chinese NMLE, NPLE and NNLE from year 2017 to 2021. In NMLE and NPLE, each exam consists of 4 units, while in NNLE, each exam consists of 2 units. The questions with figures, tables or chemical structure were manually identified and excluded by clinician. We applied direct instruction strategy via multiple prompts to force ChatGPT to generate the clear answer with the capability to distinguish between single-choice and multiple-choice questions.

Citation impact

110
total citations
FWCI
11.44
Percentile
100%
References
31
Citations per year

Authors

6

Topics & keywords

Keywords
  • Medical education
  • China
  • Significant difference
  • Pharmacist
  • Medicine
  • Educational measurement
  • Family medicine
  • Computer science
UN Sustainable Development Goals
  • Quality Education
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Funding