Evaluating the Performance of ChatGPT, Gemini, and Bing Compared with Resident Surgeons in the Otorhinolaryngology In-service Training Examination.

IF 0.7 Q4 OTORHINOLARYNGOLOGY Turkish Archives of Otorhinolaryngology Pub Date : 2024-10-23 DOI:10.4274/tao.2024.3.5
Utku Mete
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Abstract

Objective: Large language models (LLMs) are used in various fields for their ability to produce human-like text. They are particularly useful in medical education, aiding clinical management skills and exam preparation for residents. To evaluate and compare the performance of ChatGPT (GPT-4), Gemini, and Bing with each other and with otorhinolaryngology residents in answering in-service training exam questions and provide insights into the usefulness of these models in medical education and healthcare.

Methods: Eight otorhinolaryngology in-service training exams were used for comparison. 316 questions were prepared from the Resident Training Textbook of the Turkish Society of Otorhinolaryngology Head and Neck Surgery. These questions were presented to the three artificial intelligence models. The exam results were evaluated to determine the accuracy of both models and residents.

Results: GPT-4 achieved the highest accuracy among the LLMs at 54.75% (GPT-4 vs. Gemini p=0.002, GPT-4 vs. Bing p<0.001), followed by Gemini at 40.50% and Bing at 37.00% (Gemini vs. Bing p=0.327). However, senior residents outperformed all LLMs and other residents with an accuracy rate of 75.5% (p<0.001). The LLMs could only compete with junior residents. GPT- 4 and Gemini performed similarly to juniors, whose accuracy level was 46.90% (p=0.058 and p=0.120, respectively). However, juniors still outperformed Bing (p=0.019).

Conclusion: The LLMs currently have limitations in achieving the same medical accuracy as senior and mid-level residents. However, they outperform in specific subspecialties, indicating the potential usefulness in certain medical fields.

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评估 ChatGPT、Gemini 和 Bing 在耳鼻喉科在职培训考试中与住院外科医生的表现。
目的:大语言模型(LLMs)因其能够生成类人文本而被广泛应用于各个领域。它们在医学教育中尤其有用,可帮助住院医生掌握临床管理技能和备考。目的是评估和比较 ChatGPT (GPT-4)、Gemini 和 Bing 在回答耳鼻喉科住院医师在职培训考试问题时的表现,并深入了解这些模型在医学教育和医疗保健中的实用性:方法:使用八种耳鼻喉科在职培训考试进行比较。从土耳其耳鼻咽喉头颈外科协会的住院医师培训教材中准备了 316 道题。这些问题被提交给三个人工智能模型。对考试结果进行评估,以确定模型和住院医师的准确性:结果:在 LLMs 中,GPT-4 的准确率最高,达到 54.75%(GPT-4 与 Gemini 相比 p=0.002,GPT-4 与 Bing 相比 p):目前,LLM 在达到与中高级住院医师相同的医疗准确性方面存在局限性。不过,他们在特定的亚专科领域表现出色,这表明他们在某些医学领域具有潜在的实用性。
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