跳至主要内容
临床试验/NCT02748044
NCT02748044
已完成
不适用

Validation of the Utility of Rare Disease Intelligence Platform: A Multicenter Cluster Clinical Trial

Sun Yat-sen University4 个研究点 分布在 1 个国家目标入组 53 人2012年1月

概览

阶段
不适用
干预措施
未指定
疾病 / 适应症
Cataract
发起方
Sun Yat-sen University
入组人数
53
试验地点
4
主要终点
The proportion of accurate, mistaken and miss detection of CC-Cruiser.
状态
已完成
最后更新
10年前

概览

简要总结

The prevention and treatment of diseases via artificial intelligence represents an ultimate goal in computational medicine. The artificial intelligence for systematic clinical application has not yet been successfully validated. Currently, the main prevention strategy for rare diseases is to build specialized care centers. However, these centers are scattered, and their coverage is insufficient, resulting in inadequate health care among a large proportion of rare disease patients. Here, the investigators use "deep learning" to create CC-Cruiser, an intelligence agent involving three functional networks: "pick-up networks" for diagnostics, "evaluation networks" for risk stratification and "strategist networks" to provide assisted treatment decisions. The investigator also establish a cloud intelligence platform for multi-hospital collaboration and conduct clinical trial and website-based study to validate its versatility.

注册库
clinicaltrials.gov
开始日期
2012年1月
结束日期
2016年4月
最后更新
10年前
研究类型
Interventional
研究设计
Single Group
性别
All

研究者

发起方
Sun Yat-sen University
责任方
Principal Investigator
主要研究者

Erping Long

Principal Investigator, Home for Cataract Children, Zhongshan Ophthalmic Center

Sun Yat-sen University

入排标准

入选标准

  • Patients who underwent ophthalmic examination of the eye and recorded their ocular information in the collaborating hospital.

排除标准

  • 未提供

结局指标

主要结局

The proportion of accurate, mistaken and miss detection of CC-Cruiser.

时间窗: Up to 4 years

研究点 (4)

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