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

Artificial Intelligence Clinical Trial

Official title:

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

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04892316
• Other study ID #: SFLV-2020
• Status: Recruiting
• Start date: July 27, 2020
• Est. completion date: December 27, 2021

Study information

• Verified date: May 2021
• Source: Sun Yat-sen University
• Contact: Jianmin Hu, M.D., Ph.D.
• Phone: +8615359595888
• Email: doctorhjm[@]163.com
• Is FDA regulated: No
• Study type: Observational

Clinical Trial 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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 400
• Est. completion date: December 27, 2021
• Est. primary completion date: July 27, 2021
• Accepts healthy volunteers: No
• Gender: All
• Age group: 3 Years to 105 Years

Eligibility

Inclusion Criteria:

• Low vision

• Aged 3 to 105

Exclusion Criteria:

• Severe systemic disease

• Failure to sign informed consent or unwilling to participate

Related Conditions & MeSH terms

• Artificial Intelligence
• Low Vision Aids
• Ophthalmology
• Vision, Low

Intervention

Diagnostic Test:
• Diagnostic test
The training dataset was used to train the model, which was validated and tested by the other two datasets.

Locations

Country	Name	City	State
China	2nd Affilliated Hospital of Fujian Medical University	Quanzhou	Fujian

Sponsors (1)

Lead Sponsor	Collaborator
Sun Yat-sen University

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Accuracy of fitting results for assisting devices	The investigator will calculate the accuracy of fitting results for assisting devices in different group according to the ground truth.	baseline
Secondary	Time cost for fitting assisting devices	The investigator will calculate time cost for fitting assisting devices in different group.	baseline