接受生育治疗的患者对人工智能和不孕症护理的认知。

IF 3.2 3区 医学 Q2 GENETICS & HEREDITY
Sarah C Cromack, Ashley M Lew, Sarah E Bazzetta, Shuai Xu, Jessica R Walter
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引用次数: 0

摘要

目的:了解不孕症患者对人工智能(AI)在其护理中的应用意见。方法:于2024年4月至6月邀请计划或正在进行体外受精(IVF)或冷冻胚胎移植的患者完成一项匿名电子调查。该调查收集了人口统计数据、技术亲和力、对人工智能的总体看法及其在生育护理中的应用。分析了患者报告的人工智能与医生在生育护理方面的信任度(例如配子选择、促性腺激素的使用和刺激时间)。计算描述性统计,并按年龄、职业和胎次进行亚组分析。使用卡方检验比较分类变量。结果:共200例患者完成调查,主要为女性(n = 193/200),育龄(平均37岁)。患者受教育程度高,技术亲和力高。受访者熟悉人工智能(93%),普遍支持将其用于医学(55%),但较少信任人工智能知情的生殖保健(46%)。与胚胎选择相比,更多的患者(37%)不同意使用人工智能来确定促性腺激素剂量或刺激时间(26.5%;p = 0.01)。在医生和人工智能推荐不一致的情况下,患者在所有与治疗相关的决策中更倾向于医生的推荐。然而,与促性腺激素剂量(6.5%)或刺激长度(7.0%)相比,更大比例的人支持人工智能对配子(22%)和胚胎(14.5%)选择的建议。大多数人不愿意为人工智能生育护理支付更多费用。结论:在这个熟悉人工智能的高学历不育人群中,与人工智能相比,患者仍然更倾向于基于医生的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The perception of artificial intelligence and infertility care among patients undergoing fertility treatment.

Purpose: To characterize the opinions of patients undergoing infertility treatment on the use of artificial intelligence (AI) in their care.

Methods: Patients planning or undergoing in vitro fertilization (IVF) or frozen embryo transfers were invited to complete an anonymous electronic survey from April to June 2024. The survey collected demographics, technological affinity, general perception of AI, and its applications to fertility care. Patient-reported trust of AI compared to a physician for fertility care (e.g. gamete selection, gonadotropin doing, and stimulation length) were analyzed. Descriptive statistics were calculated, and subgroup analyses by age, occupation, and parity were performed. Chi-squared tests were used to compare categorical variables.

Results: A total of 200 patients completed the survey and were primarily female (n = 193/200) and of reproductive age (mean 37 years). Patients were well educated with high technological affinity. Respondents were familiar with AI (93%) and generally supported its use in medicine (55%), but fewer trusted AI-informed reproductive care (46%). More patients disagreed (37%) that AI should be used to determine gonadotropin dose or stimulation length compared to embryo selection (26.5%; p = 0.01). In the setting of disagreement between physician and AI recommendation, patients preferred the physician-based recommendation in all treatment-related decisions. However, a larger proportion favored AI recommendations for gamete (22%) and embryo (14.5%) selection, compared to gonadotropin dosing (6.5%) or stimulation length (7.0%). Most would not be willing to pay more for AI-informed fertility care.

Conclusions: In this highly educated infertile population familiar with AI, patients still prefer physician-based recommendations compared with AI.

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来源期刊
CiteScore
5.70
自引率
9.70%
发文量
286
审稿时长
1 months
期刊介绍: The Journal of Assisted Reproduction and Genetics publishes cellular, molecular, genetic, and epigenetic discoveries advancing our understanding of the biology and underlying mechanisms from gametogenesis to offspring health. Special emphasis is placed on the practice and evolution of assisted reproduction technologies (ARTs) with reference to the diagnosis and management of diseases affecting fertility. Our goal is to educate our readership in the translation of basic and clinical discoveries made from human or relevant animal models to the safe and efficacious practice of human ARTs. The scientific rigor and ethical standards embraced by the JARG editorial team ensures a broad international base of expertise guiding the marriage of contemporary clinical research paradigms with basic science discovery. JARG publishes original papers, minireviews, case reports, and opinion pieces often combined into special topic issues that will educate clinicians and scientists with interests in the mechanisms of human development that bear on the treatment of infertility and emerging innovations in human ARTs. The guiding principles of male and female reproductive health impacting pre- and post-conceptional viability and developmental potential are emphasized within the purview of human reproductive health in current and future generations of our species. The journal is published in cooperation with the American Society for Reproductive Medicine, an organization of more than 8,000 physicians, researchers, nurses, technicians and other professionals dedicated to advancing knowledge and expertise in reproductive biology.
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