Clinical trial NCT02748044: Validation of the Utility of Rare Disease Intelligence Platform
Official title: Validation of the Utility of Rare Disease Intelligence Platform: A Multicenter Cluster Clinical Trial
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Cataract
Artificial Intelligence
Lead sponsor: Sun Yat-sen University
Sponsor class: OTHER
Collaborators: name: Ministry of Health, China
name: Xidian University
First posted: 2016-04-22
Enrollment: 53
Sex: ALL
Maximum age (years): 80
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Primary purpose: DIAGNOSTIC

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.


Eligibility criteria: Inclusion Criteria:

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

Exclusion Criteria:

-

Primary outcomes:
measure: The proportion of accurate, mistaken and miss detection of CC-Cruiser.
timeFrame: Up to 4 years
Secondary outcomes:
Other outcomes:
Locations:
city: Guangzhou
country: China
facility: Zhongshan Ophthalmic Center, Sun Yat-sen University
state: Guangdong
city: Guangzhou
country: China
facility: Department of Ophthalmology, Guangdong General Hospital, Guangdong Academy of Medical Sciences
state: Guangdong
city: Guangzhou
country: China
facility: Department of Ophthalmology, First Affiliated Hospital, Guangzhou University of Traditional Chinese Medicine
state: Guangdong
city: Qingyuan
country: China
facility: Department of Ophthalmology, Qingyuan People's Hospital
state: Guangdong
Study officials:
affiliation: Zhongshan Ophthalmic Center, Sun Yat-sen University
name: Haotian Lin, M.D., Ph.D
role: STUDY_DIRECTOR
affiliation: Zhongshan Ophthalmic Center, Sun Yat-sen University
name: Yizhi Liu, M.D., Ph.D
role: STUDY_CHAIR
affiliation: Zhongshan Ophthalmic Center, Sun Yat-sen University
name: Erping Long, M.D., Ph.D
role: PRINCIPAL_INVESTIGATOR
References:
citation: 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.
citation: 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.