人工智能 (AI) 目前是否能够就可以改善胚胎移植结果的方法提供基于证据的科学回应?不能。

IF 1.8 Q3 OBSTETRICS & GYNECOLOGY
Argyrios Kolokythas, Michael H Dahan
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引用次数: 0

摘要

目的:人工智能(AI)的快速发展引发了人们对其在日常生活不同领域的潜在用途的疑问。特别是在医学领域,聊天机器人是否可用作临床决策或患者和医生教育的工具成为一个问题。为了在生育领域回答这个问题,我们进行了一项测试,以确定当前的人工智能平台是否能就可改善胚胎移植结果的方法提供基于证据的回复:我们要求九个流行的聊天机器人撰写一篇 300 字的科学论文,概述可改善胚胎移植结果的科学方法。然后我们收集了回复,并提取了每个聊天机器人建议的方法:结果:在总共 43 条建议(可分为 19 个类似类别)中,只有 3/19(15.8%)条是循证做法,分别是 7/9(77.8%)个聊天机器人提出的 "超声引导下胚胎移植"、4/9(44.4%)个聊天机器人提出的 "单胚胎移植 "和 2/9(22.2%)个聊天机器人提出的 "使用软导管"。2%),而 "植入前基因检测 "等一些有争议的回答则经常出现(6/9 个聊天机器人;66.7%),还有 "子宫内膜受孕率检测"、"辅助孵化 "和 "延时孵化器 "等其他有争议的建议:我们的研究结果表明,人工智能还不能在生育领域,尤其是胚胎移植方面提供循证建议,因为绝大多数回复都是没有科学依据的建议。因此,患者和医生在根据聊天机器人的建议指导不孕不育治疗时都应保持警惕。随着时间的推移,聊天机器人的结果可能会有所改善,特别是如果从经过验证的医疗数据库中进行培训的话;不过,这还需要经过科学检验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Is Artificial Intelligence (AI) currently able to provide evidence-based scientific responses on methods that can improve the outcomes of embryo transfers? No.

Objective: The rapid development of Artificial Intelligence (AI) has raised questions about its potential uses in different sectors of everyday life. Specifically in medicine, the question arose whether chatbots could be used as tools for clinical decision-making or patients' and physicians' education. To answer this question in the context of fertility, we conducted a test to determine whether current AI platforms can provide evidence-based responses regarding methods that can improve the outcomes of embryo transfers.

Methods: We asked nine popular chatbots to write a 300-word scientific essay, outlining scientific methods that improve embryo transfer outcomes. We then gathered the responses and extracted the methods suggested by each chatbot.

Results: Out of a total of 43 recommendations, which could be grouped into 19 similar categories, only 3/19 (15.8%) were evidence-based practices, those being "ultrasound-guided embryo transfer" in 7/9 (77.8%) chatbots, "single embryo transfer" in 4/9 (44.4%) and "use of a soft catheter" in 2/9 (22.2%), whereas some controversial responses like "preimplantation genetic testing" appeared frequently (6/9 chatbots; 66.7%), along with other debatable recommendations like "endometrial receptivity assay", "assisted hatching" and "time-lapse incubator".

Conclusions: Our results suggest that AI is not yet in a position to give evidence-based recommendations in the field of fertility, particularly concerning embryo transfer, since the vast majority of responses consisted of scientifically unsupported recommendations. As such, both patients and physicians should be wary of guiding care based on chatbot recommendations in infertility. Chatbot results might improve with time especially if trained from validated medical databases; however, this will have to be scientifically checked.

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来源期刊
CiteScore
3.30
自引率
6.70%
发文量
56
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