Validation of the Utility of Rare Disease Intelligence Platform

Not Applicable

Completed

• Conditions: Cataract; Artificial Intelligence

• Registration Number: NCT02748044
• Lead Sponsor: Sun Yat-sen University

Brief Summary

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.

Detailed Description

Not available

Study Timeline

• Study Start: 2012-01
• Status Verified: 2016-04
• Primary Completion: 2016-04
• Study Completion: 2016-04
• Study First Submitted: 2016-04-13
• Study First Submitted QC: 2016-04-21
• Last Update Submitted: 2016-04-21
• Study First Posted: 2016-04-22
• Last Update Posted: 2016-04-22

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 53

Inclusion Criteria

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

Exclusion Criteria

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: SINGLE_GROUP

Primary Outcome Measures

Name	Time	Method
The proportion of accurate, mistaken and miss detection of CC-Cruiser.	Up to 4 years

Trial Locations

Locations (4)

Zhongshan Ophthalmic Center, Sun Yat-sen University; 🇨🇳 Guangzhou, Guangdong, China

Department of Ophthalmology, Guangdong General Hospital, Guangdong Academy of Medical Sciences; 🇨🇳 Guangzhou, Guangdong, China

Department of Ophthalmology, First Affiliated Hospital, Guangzhou University of Traditional Chinese Medicine; 🇨🇳 Guangzhou, Guangdong, China

Department of Ophthalmology, Qingyuan People's Hospital; 🇨🇳 Qingyuan, Guangdong, China