Using Machine Learning to Adapt Visual Aids for Patients With Low Vision

  • STATUS
    Recruiting
  • participants needed
    400
  • sponsor
    Sun Yat-sen University
Updated on 26 January 2022

Summary

According to the WHO's definition of visual impairment, as of 2018, there were approximately 1.3 billion people with visual impairment in the world, and only 10% of countries can provide assisting services for the rehabilitation of visual impairment. Although China is one of the countries that can provide rehabilitation services for patients with visual impairment, due to restrictions on the number of professionals in various regions, uneven diagnosis and treatment, and regional differences in economic conditions, not all visually impaired patients can get the rehabilitation of assisting device fitting.

Traditional statistical methods were not enough to solve the problem of intelligent fitting of assisting devices. At present, there are almost no intelligent fitting models of assisting devices in the world. Therefore, in order to allow more low-vision patients to receive accurate and rapid rehabilitation services, we conducted a cross-sectional study on the assisting devices fitting for low-vision patients in Fujian Province, China in the past five years, and at the same time constructed a machine learning model to intelligently predict the adaptation result of the basic assisting devices for low vision patients.

Details
Condition Low Vision Aids, Artificial Intelligence, Ophthalmology
Treatment Diagnostic Test
Clinical Study IdentifierNCT04892316
SponsorSun Yat-sen University
Last Modified on26 January 2022

Similar trials to consider

Loading...

Not finding what you're looking for?

Every year hundreds of thousands of volunteers step forward to participate in research. Sign up as a volunteer and receive email notifications when clinical trials are posted in the medical category of interest to you.

Sign up as volunteer

user name

Added by • 

 • 

Private

Reply by • Private
Loading...

Lorem ipsum dolor sit amet consectetur, adipisicing elit. Ipsa vel nobis alias. Quae eveniet velit voluptate quo doloribus maxime et dicta in sequi, corporis quod. Ea, dolor eius? Dolore, vel!

  The passcode will expire in None.
Loading...

No annotations made yet

Add a private note
  • abc Select a piece of text from the left.
  • Add notes visible only to you.
  • Send it to people through a passcode protected link.
Add a private note