Assessment of Artificial Intelligence Platforms With Regard to Medical Microbiology Knowledge: An Analysis of ChatGPT and Gemini

被引：4

作者：

Ranjan, Jai ^{[1
]}

Ahmad, Absar ^{[2
]}

Subudhi, Monalisa ^{[3
]}

Kumar, Ajay ^{[4
]}

机构：

[1] All India Inst Med Sci, Microbiol, Bathinda, India

[2] Birsa Agr Univ, Fac Vet Sci & Anim Husb, Anim Genet & Breeding, Ranchi, India

[3] Inst Med Sci & SUM II Hosp, Microbiol, Bhubaneswar, India

[4] Manipal Acad Higher Educ, Manipal Tata Med Coll, Pediat, Manipal, India

来源：

CUREUS JOURNAL OF MEDICAL SCIENCE | 2024年 / 16卷 / 05期

关键词：

learning; large language model; artificial intelligence; medical education; microbiology;

D O I：

10.7759/cureus.60675

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

The performance of two artificial intelligence (AI) platforms, ChatGPT 3.5 (OpenAI, California, United States) and Gemini (Google AI, California, United States) was assessed by answering 200 questions of microbiology drawn from validated sources. The questions were selected from topics such as General Microbiology, Immunology, and Microbiology Applied to Infectious Diseases. The study was conducted from December 2023 to March 2024, and the responses of the different AI platforms were compared with an answer key. Statistical analysis was performed to assess accuracy. ChatGPT 3.5 and Gemini had comparable accuracy with correct response scores of 71% and 70.5%, respectively. Their performance varied across different sections. Gemini performed better in General Microbiology and Immunology, and ChatGPT 3.5 had a better score in the Applied Microbiology section. The study's findings highlight that AI platforms such as ChatGPT and Gemini can be utilized in microbiology and medical education. The evolution and continuous updating of AI platforms are required to improve their performance.

引用

页数：6

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