人工智能聊天机器人在牙髓和牙周诊断中的准确性比较：横断面研究

IF 7 2区医学 Q1 BIOLOGY

Computers in biology and medicine Pub Date : 2024-10-30 DOI:10.1016/j.compbiomed.2024.109332

João Daniel Mendonça de Moura , Carlos Eduardo Fontana , Vitor Henrique Reis da Silva Lima , Iris de Souza Alves , Paulo André de Melo Santos , Patrícia de Almeida Rodrigues

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引用次数: 0

摘要

研究目的本研究旨在评估四个人工智能聊天机器人在虚构的牙髓和牙周疾病病例中的诊断准确性和治疗建议性能。此外，它还调查了回复的一致性以及文本顺序和语言对聊天机器人性能的影响：在这项横向比较研究中，创建了 11 个代表各种牙髓和牙周疾病的案例。这些病例以葡萄牙语和英语呈现给四个聊天机器人（ChatGPT 3.5、ChatGPT 4.0、Bard 和 Bing），信息顺序各不相同（先有体征和症状还是先有成像数据）。统计分析包括 Kruskal-Wallis 检验、Dwass-Steel-Critchlow-Fligner 配对比较、简单逻辑回归和二项式检验：必应和 ChatGPT 4.0 的诊断准确率最高（分别为 86.4 % 和 85.3 %），明显优于 ChatGPT 3.5（46.5 %）和 Bard（28.6 %）（P 结论：必应和 ChatGPT 4.0 的诊断准确率分别为 86.4 % 和 85.3 %，明显优于 ChatGPT 3.5（46.5 %）和 Bard（28.6 %）：Bing 和 ChatGPT 4.0 的诊断准确率更高，而 Bard 在诊断和治疗建议方面的准确率最低。但是，这些工具的临床应用需要牙医的严格解释，因为聊天机器人的回复并不总是可靠的。

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查看原文本刊更多论文

Comparative accuracy of artificial intelligence chatbots in pulpal and periradicular diagnosis: A cross-sectional study

Objectives

This study aimed to evaluate the diagnostic accuracy and treatment recommendation performance of four artificial intelligence chatbots in fictional pulpal and periradicular disease cases. Additionally, it investigated response consistency and the influence of text order and language on chatbot performance.

Methods

In this cross-sectional comparative study, eleven cases representing various pulpal and periradicular pathologies were created. These cases were presented to four chatbots (ChatGPT 3.5, ChatGPT 4.0, Bard, and Bing) in both Portuguese and English, with the information order varied (signs and symptoms first or imaging data first). Statistical analyses included the Kruskal-Wallis test, Dwass-Steel-Critchlow-Fligner pairwise comparisons, simple logistic regression, and the binomial test.

Results

Bing and ChatGPT 4.0 achieved the highest diagnostic accuracy rates (86.4 % and 85.3 % respectively), significantly outperforming ChatGPT 3.5 (46.5 %) and Bard (28.6 %) (p < 0.001). For treatment recommendations, ChatGPT 4.0, Bing, and ChatGPT 3.5 performed similarly (94.4 %, 93.2 %, and 86.3 %, respectively), while Bard exhibited significantly lower accuracy (75 %, p < 0.001). No significant association between diagnosis and treatment accuracy was found for Bard and Bing, but a positive association was observed for ChatGPT 3.5 and ChatGPT 4.0 (p < 0.05). The overall consistency rate was 98.29 %, with no significant differences related to text order or language. Cases presented in Portuguese prompted significantly more additional information requests than those in English (33.5 % vs. 10.2 %; p < 0.001), with the relevance of this information being higher in Portuguese (29.5 % vs. 8.5 %; p < 0.001).

Conclusions

Bing and ChatGPT 4.0 demonstrated superior diagnostic accuracy, while Bard showed the lowest accuracy in both diagnosis and treatment recommendations. However, the clinical application of these tools necessitates critical interpretation by dentists, as chatbot responses are not consistently reliable.

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来源期刊

Computers in biology and medicine 工程技术-工程：生物医学

CiteScore

11.70

自引率

10.40%

发文量

1086

审稿时长

74 days

期刊介绍： Computers in Biology and Medicine is an international forum for sharing groundbreaking advancements in the use of computers in bioscience and medicine. This journal serves as a medium for communicating essential research, instruction, ideas, and information regarding the rapidly evolving field of computer applications in these domains. By encouraging the exchange of knowledge, we aim to facilitate progress and innovation in the utilization of computers in biology and medicine.