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儿童糖尿病人工智能应用的透明度和有效性:系统性审查

Belgees Altigani Hamza Yousif^1,2, Almontasir Belah Alsadig Abdalwahab Abdallah³, Aya Abuelgasim Ibrahim Abdelhalim⁴

¹Faculty of Medicine, Algadarif University, Gadarif, SDN.

|September 2, 2025

概括

人工智能 (AI) 在儿童糖尿病治疗方面显得有前途. 然而,不一致的透明度和有限的验证阻碍了其临床使用,需要标准化的报告和可靠的验证.

科学领域:

儿童内分泌学
医疗信息学
医疗保健中的人工智能

背景情况:

人工智能 (AI) 提供了儿童糖尿病管理方面的潜在进展.
目前,人工智能工具的临床采用受到透明度和有效性方面的担忧的限制.
对人工智能的透明度和有效性的系统评估很少.

研究的目的:

系统地审查儿童糖尿病管理中使用的AI应用程序的透明度和有效性.
评估现有人工智能研究的方法严谨性,报告标准和临床准备.
识别缺口,并为未来儿童糖尿病人工智能开发和实施提供建议.

主要方法:

根据PRISMA 2020指南进行系统审查.
搜索了主要的科学数据库 (Scopus,PubMed,IEEE Xplore,科学网,Embase).
包括10项儿童糖尿病人工智能研究,评估透明度,验证和偏差风险 (QUADAS-2).

主要成果:

人工智能应用包括葡萄糖预测,低血糖风险和胰岛素剂量.
透明度不同,只有60%的算法细节被披露.
只有30%的研究存在外部验证,40%的人对偏差风险表示担忧.
算法不透明性和小的验证队列被认为是局限性的.

结论:

人工智能在儿童糖尿病管理方面具有显著的潜力.
不一致的透明度和不足的验证阻碍了临床转化.
未来的研究应该集中在标准化报告,多中心验证和多样化的群体上,以确保人工智能的可靠性和公平性.

关键词:

人工智能机器学习儿童糖尿病系统审查透明度有效期

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