基于人工智能的早产儿视网膜病变诊断算法。

IF 8.8 2区 医学 Q1 MEDICINE, GENERAL & INTERNAL
Paul Chong, Benjamin K Young, Stephen McNamara, Sueko M Ng, Su-Hsun Liu, Tianjing Li, J Peter Campbell, Jayashree Kalpathy-Cramer, Praveer Singh
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引用次数: 0

摘要

目的:这是Cochrane综述(诊断)的一份方案。本研究的目的如下:对比现有的ROP临床诊断标签参考标准,评估基于人工智能的算法的诊断性能。次要目标通过亚组分析,对影响模型性能的潜在异质性来源进行严格检查:研究人群的人口统计学(种族或民族);输入数据的类型(仅图像,仅临床变量,或两者的组合);人工智能算法(CNN或DNN)采用的基本方法;扫描仪类型(Retcam、Forus或phoenix ICON)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Artificial intelligence-based algorithms for the diagnosis of retinopathy of prematurity.

Artificial intelligence-based algorithms for the diagnosis of retinopathy of prematurity.

Objectives: This is a protocol for a Cochrane Review (diagnostic). The objectives are as follows: To assess the diagnostic performance of AI-based algorithms in comparison to the established reference standard of clinical diagnosis labels for ROP. Secondary objectives To undertake a critical examination of potential sources of heterogeneity influencing model performance by conducting subgroup analysis by: demographics of the study population (race or ethnicity); type of input data (images only, clinical variables only, or a combination of both); the fundamental methodologies adopted by the AI algorithms (CNN or DNN); and scanner type (Retcam, Forus, or Pheonix ICON).

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来源期刊
CiteScore
10.60
自引率
2.40%
发文量
173
审稿时长
1-2 weeks
期刊介绍: The Cochrane Database of Systematic Reviews (CDSR) stands as the premier database for systematic reviews in healthcare. It comprises Cochrane Reviews, along with protocols for these reviews, editorials, and supplements. Owned and operated by Cochrane, a worldwide independent network of healthcare stakeholders, the CDSR (ISSN 1469-493X) encompasses a broad spectrum of health-related topics, including health services.
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