A Big Data-based Cohort Study for Cataract Patients

  • days left to enroll
  • participants needed
  • sponsor
    Sun Yat-sen University
Updated on 4 October 2022
visual impairment
intraocular lens implantation


Cataract is an important cause of blindness and visual impairment worldwide. At present, the only effective treatment method is surgery. The visual function of most patients can be significantly improved after surgery, but there are still 5-20% of patients whose visual function cannot be improved after surgery. Previous studies have found that the surgical complications and postoperative visual function of cataract patients are closely related to the condition of the fundus, but the current fundus camera cannot perform clear fundus imaging of cataract patients, and the existing potential visual inspections, such as retinal visual inspection, are also inaccurate. Predict postoperative visual acuity. Therefore, there is an urgent need for a reliable postoperative effect prediction system for cataract patients to provide reference for both ophthalmologists and patients.

This study intends to collect patient medical record information and traditional/ultra-wide fundus photos and other multi-modal data. Firstly, this study will use artificial intelligence technology to enhance fundus photos of cataract patients to obtain clearer fundus photos. Then this study will use both medical record information and traditional/ultra-wide fundus photographs to predict postoperative vision and visual function of cataract patients.

Condition Cataract, Retina Disorder
Clinical Study IdentifierNCT05491798
SponsorSun Yat-sen University
Last Modified on4 October 2022


Yes No Not Sure

Inclusion Criteria

Candidates for cataract surgery (phacoemulsification and intraocular lens implantation) within a week

Exclusion Criteria

Unwilling or unable to receive fundus photography
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Complete your scheduled study participation activities and then you are done. You may receive summary of study results if provided by the sponsor.

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