NCT02748044

Validation of the Utility of Rare Disease Intelligence Platform

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

• Status: Completed
• Phase: N/A
• Study type: Interventional
• Enrollment: 53 (actual)
• Sponsor: Sun Yat-sen University · Academic / Other
• Sex: All
• Age: 80 Years
• Healthy volunteers: Not accepted

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.

Conditions

• Cataract
• Artificial Intelligence

Interventions

Type	Name	Description
DEVICE	CC-Cruiser	An artificial intelligence to make comprehensive evaluation and treatment decision of congenital cataracts

Timeline

• Start date: 2012-01-01
• Primary completion: 2016-04-01
• Completion: 2016-04-01
• First posted: 2016-04-22
• Last updated: 2016-04-22

Locations

4 sites across 1 country: China