NCT02748044

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.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
53

participants targeted

Target at P25-P50 for not_applicable

Timeline
Completed

Started Jan 2012

Longer than P75 for not_applicable

Geographic Reach
1 country

4 active sites

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

January 1, 2012

Completed
4.3 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

April 1, 2016

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

April 1, 2016

Completed
12 days until next milestone

First Submitted

Initial submission to the registry

April 13, 2016

Completed
9 days until next milestone

First Posted

Study publicly available on registry

April 22, 2016

Completed
Last Updated

April 22, 2016

Status Verified

April 1, 2016

Enrollment Period

4.3 years

First QC Date

April 13, 2016

Last Update Submit

April 21, 2016

Conditions

CataractArtificial Intelligence

Outcome Measures

Primary Outcomes (1)

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

    Up to 4 years

Study Arms (1)

Eligible patients for CC-Cruiser test

EXPERIMENTAL
Device: CC-Cruiser

Interventions

CC-CruiserDEVICE

An artificial intelligence to make comprehensive evaluation and treatment decision of congenital cataracts

Eligible patients for CC-Cruiser test

Eligibility Criteria

AgeUp to 80 Years
Sexall
Healthy VolunteersNo
Age GroupsChild (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

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

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (4)

Zhongshan Ophthalmic Center, Sun Yat-sen University

Guangzhou, Guangdong, 510060, China

Location

Department of Ophthalmology, Guangdong General Hospital, Guangdong Academy of Medical Sciences

Guangzhou, Guangdong, 510080, China

Location

Department of Ophthalmology, First Affiliated Hospital, Guangzhou University of Traditional Chinese Medicine

Guangzhou, Guangdong, 510405, China

Location

Department of Ophthalmology, Qingyuan People's Hospital

Qingyuan, Guangdong, 511518, China

Location

Related Publications (2)

  • Lin H, Long E, Chen W, Liu Y. Documenting rare disease data in China. Science. 2015 Sep 4;349(6252):1064. doi: 10.1126/science.349.6252.1064-b. No abstract available.

    PMID: 26339020BACKGROUND

  • Lin H, Ouyang H, Zhu J, Huang S, Liu Z, Chen S, Cao G, Li G, Signer RA, Xu Y, Chung C, Zhang Y, Lin D, Patel S, Wu F, Cai H, Hou J, Wen C, Jafari M, Liu X, Luo L, Zhu J, Qiu A, Hou R, Chen B, Chen J, Granet D, Heichel C, Shang F, Li X, Krawczyk M, Skowronska-Krawczyk D, Wang Y, Shi W, Chen D, Zhong Z, Zhong S, Zhang L, Chen S, Morrison SJ, Maas RL, Zhang K, Liu Y. Lens regeneration using endogenous stem cells with gain of visual function. Nature. 2016 Mar 17;531(7594):323-8. doi: 10.1038/nature17181. Epub 2016 Mar 9.

    PMID: 26958831BACKGROUND

Related Links

MeSH Terms

Conditions

Cataract

Condition Hierarchy (Ancestors)

Lens DiseasesEye Diseases

Study Officials

  • Haotian Lin, M.D., Ph.D

    Zhongshan Ophthalmic Center, Sun Yat-sen University

    STUDY DIRECTOR

  • Yizhi Liu, M.D., Ph.D

    Zhongshan Ophthalmic Center, Sun Yat-sen University

    STUDY CHAIR

  • Erping Long, M.D., Ph.D

    Zhongshan Ophthalmic Center, Sun Yat-sen University

    PRINCIPAL INVESTIGATOR

Study Design

Study Type
interventional
Phase
not applicable
Allocation
NA
Masking
NONE
Purpose
DIAGNOSTIC
Intervention Model
SINGLE GROUP
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Principal Investigator, Home for Cataract Children, Zhongshan Ophthalmic Center

Study Record Dates

First Submitted

April 13, 2016

First Posted

April 22, 2016

Study Start

January 1, 2012

Primary Completion

April 1, 2016

Study Completion

April 1, 2016

Last Updated

April 22, 2016

Record last verified: 2016-04

Locations

CN(4)