Validation of an Artificial Intelligence System for Postoperative Management of Cataract Patients

Sponsor
Sun Yat-sen University (Other)
Overall Status
Recruiting
CT.gov ID
NCT04138771
Collaborator
Ministry of Health, China (Other), Xidian University (Other)
300
Enrollment
1
Location
1
Arm
85.9
Duration (Months)
3.5
Patients Per Site Per Month

Study Details

Study Description

Brief Summary

Cataract surgery is the current standard of management for cataract patients, which is typically succeeded by a postoperative follow-up schedule. Here, the investigators established and validated an artificial intelligence system to achieve automatic management of postoperative patients based on analyses of visual acuity, intraocular pressure and slit-lamp images. The management strategy can also change according to postoperative time.

Condition or DiseaseIntervention/TreatmentPhase
  • Device: An artificial intelligence system for postoperative management of cataract patients
N/A

Study Design

Study Type:
Interventional
Anticipated Enrollment :
300 participants
Allocation:
N/A
Intervention Model:
Single Group Assignment
Masking:
None (Open Label)
Primary Purpose:
Diagnostic
Official Title:
Validation of an Artificial Intelligence System for Postoperative Management of Cataract Patients: A Clinical Trial
Study Start Date :
Jan 1, 2013
Anticipated Primary Completion Date :
Mar 1, 2020
Anticipated Study Completion Date :
Mar 1, 2020

Arms and Interventions

ArmIntervention/Treatment
Experimental: Eligible patients for AI test

Device: an artificial intelligence system for postoperative management of cataract patients. These patients are enrolled in primary healthcare units and the AI clinic at Zhongshan Ophthalmic Center.

Device: An artificial intelligence system for postoperative management of cataract patients
This system can detect multiple postoperative complications of cataract patients and then provide a management strategy.

Outcome Measures

Primary Outcome Measures

  1. The proportion of accurate, mistaken and miss detection of this artificial intelligence diagnostic system. [Up to 7 years]

Eligibility Criteria

Criteria

Ages Eligible for Study:
N/A and Older
Sexes Eligible for Study:
All
Accepts Healthy Volunteers:
No
Inclusion Criteria:
  • Patients who had surgery of cataract extraction combined with introcular lens implantation.

  • Patients should be aware of the contents and signed for the informed consent.

Contacts and Locations

Locations

SiteCityStateCountryPostal Code
1Zhongshan Ophthalmic Center, Sun Yat-sen UniversityGuangzhouGuangdongChina510060

Sponsors and Collaborators

  • Sun Yat-sen University
  • Ministry of Health, China
  • Xidian University

Investigators

None specified.

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.
Responsible Party:
Haotian Lin, Clinical Professor, Sun Yat-sen University
ClinicalTrials.gov Identifier:
NCT04138771
Other Study ID Numbers:
  • CCPMOH2019-China-5
First Posted:
Oct 24, 2019
Last Update Posted:
Dec 3, 2019
Last Verified:
Dec 1, 2019
Studies a U.S. FDA-regulated Drug Product:
No
Studies a U.S. FDA-regulated Device Product:
No
Keywords provided by Haotian Lin, Clinical Professor, Sun Yat-sen University
Additional relevant MeSH terms:

Study Results

No Results Posted as of Dec 3, 2019