Ignite Creation Date:
2024-05-06 @ 4:13 PM
Last Modification Date:
2024-10-26 @ 2:06 PM
Study NCT ID:
NCT04919837
Status:
UNKNOWN
Last Update Posted:
2021-06-09
First Post:
2021-06-06
Brief Title:
The Efficacy of an Artificial Intelligence Platform to Adapt Visual Aids for Patients With Low Vision a Randomised Controlled Trial
Sponsor:
Sun Yat-sen University
Organization:
Sun Yat-sen University
Study Overview
Official Title:
The Efficacy of an Artificial Intelligence Platform to Adapt Visual Aids for Patients With Low Vision a Randomised Controlled Trial
Status:
UNKNOWN
Status Verified Date:
2021-06
Last Known Status:
RECRUITING
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
AI
Brief Summary:
According to the WHOs definition of visual impairment as of 2018 there were approximately 13 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
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
Detailed Description:
None
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None