- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT02748044
Validation of the Utility of Rare Disease Intelligence Platform
April 21, 2016 updated by: Erping Long, Sun Yat-sen University
Validation of the Utility of Rare Disease Intelligence Platform: A Multicenter Cluster Clinical Trial
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.
Study Overview
Status
Completed
Conditions
Intervention / Treatment
Study Type
Interventional
Enrollment (Actual)
53
Phase
- Not Applicable
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Locations
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-
Guangdong
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Guangzhou, Guangdong, China, 510060
- Zhongshan Ophthalmic Center, Sun Yat-sen University
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Guangzhou, Guangdong, China, 510080
- Department of Ophthalmology, Guangdong General Hospital, Guangdong Academy of Medical Sciences
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Guangzhou, Guangdong, China, 510405
- Department of Ophthalmology, First Affiliated Hospital, Guangzhou University of Traditional Chinese Medicine
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Qingyuan, Guangdong, China, 511518
- Department of Ophthalmology, Qingyuan People's Hospital
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-
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
No older than 80 years (Child, Adult, Older Adult)
Accepts Healthy Volunteers
No
Genders Eligible for Study
All
Description
Inclusion Criteria:
- Patients who underwent ophthalmic examination of the eye and recorded their ocular information in the collaborating hospital.
Exclusion Criteria:
-
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
- Primary Purpose: Diagnostic
- Allocation: N/A
- Interventional Model: Single Group Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
---|---|
Experimental: Eligible patients for CC-Cruiser test
|
An artificial intelligence to make comprehensive evaluation and treatment decision of congenital cataracts
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Time Frame |
---|---|
The proportion of accurate, mistaken and miss detection of CC-Cruiser.
Time Frame: Up to 4 years
|
Up to 4 years
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Investigators
- Principal Investigator: Erping Long, M.D., Ph.D, Zhongshan Ophthalmic Center, Sun Yat-sen University
- Study Director: Haotian Lin, M.D., Ph.D, Zhongshan Ophthalmic Center, Sun Yat-sen University
Publications and helpful links
The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.
General Publications
- 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.
- 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. Erratum In: Nature. 2017 Jan 26;541(7638):558.
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start
January 1, 2012
Primary Completion (Actual)
April 1, 2016
Study Completion (Actual)
April 1, 2016
Study Registration Dates
First Submitted
April 13, 2016
First Submitted That Met QC Criteria
April 21, 2016
First Posted (Estimate)
April 22, 2016
Study Record Updates
Last Update Posted (Estimate)
April 22, 2016
Last Update Submitted That Met QC Criteria
April 21, 2016
Last Verified
April 1, 2016
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- CCPMOH2016-China3
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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