Artificial Intelligence Clinical Trial
Official title:
Using Machine Learning to Adapt Visual Aids for Patients With Low Vision
NCT number | NCT04892316 |
Other study ID # | SFLV-2020 |
Secondary ID | |
Status | Recruiting |
Phase | |
First received | |
Last updated | |
Start date | July 27, 2020 |
Est. completion date | December 27, 2021 |
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.
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 |
Country | Name | City | State |
---|---|---|---|
China | 2nd Affilliated Hospital of Fujian Medical University | Quanzhou | Fujian |
Lead Sponsor | Collaborator |
---|---|
Sun Yat-sen University |
China,
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 |
Status | Clinical Trial | Phase | |
---|---|---|---|
Completed |
NCT04589078 -
Polyp REcognition Assisted by a Device Interactive Characterization Tool - The PREDICT Study
|
||
Completed |
NCT03857438 -
Correlation of Audiovisual Features With Clinical Variables and Neurocognitive Functions in Bipolar Disorder, Mania
|
||
Completed |
NCT04735055 -
Artificial Intelligence Prediction for the Severity of Acute Pancreatitis
|
||
Not yet recruiting |
NCT05452993 -
Screening for Diabetic Retinopathy in Pharmacies With Artificial Intelligence Enhanced Retinophotography
|
N/A | |
Not yet recruiting |
NCT04337229 -
Evaluation of Comfort Behavior Levels of Newborns With Artificial Intelligence Techniques
|
N/A | |
Completed |
NCT05687318 -
A Clinical Trial of the Effectiveness and Safety of Software Assisting Diagnose the Intestinal Polyp Digestive Endoscopy by Analysis of Colonoscopy Medical Images From Electronic Digestive Endoscopy Equipment
|
N/A | |
Recruiting |
NCT06051682 -
Optimization of the Diagnosis of Bone Fractures in Patients Treated in the Emergency Department by Using Artificial Intelligence for Reading Radiological Images in Comparison With Traditional Reading by the Emergency Doctor.
|
N/A | |
Not yet recruiting |
NCT06039917 -
Effect of the Automatic Surveillance System on Surveillance Rate of Patients With Gastric Premalignant Lesions
|
N/A | |
Not yet recruiting |
NCT06362629 -
AI App for Management of Atopic Dermatitis
|
N/A | |
Recruiting |
NCT06059378 -
Real-life Implementation of an AI-based Optical Diagnosis
|
N/A | |
Recruiting |
NCT06164002 -
A I in the Prediction of Clinical Performance, Marginal Fit and Fracture Resistance of Vertical Versus Horizontal Margin Designs Fabricated With 2 Ceramic Materials
|
N/A | |
Completed |
NCT05517889 -
Repeatability and Stability of Healthy Skin Features on OCT
|
||
Completed |
NCT04816981 -
AI-EBUS-Elastography for LN Staging
|
N/A | |
Completed |
NCT05006092 -
Surveillance Modified by Artificial Intelligence in Endoscopy (SMARTIE)
|
N/A | |
Recruiting |
NCT04535466 -
Diagnosis Predictive Modle for Dense Density Breast Tissue Based on Radiomics
|
||
Enrolling by invitation |
NCT04719117 -
Retrograde Cholangiopancreatography AI Assisted System Validation on Effectiveness and Safety
|
||
Completed |
NCT04399590 -
Comparing the Number of False Activations Between Two Artificial Intelligence CADe Systems: the NOISE Study
|
||
Recruiting |
NCT04126265 -
Artificial Intelligence-assisted Colonoscopy for Detection of Colon Polyps
|
N/A | |
Recruiting |
NCT06255808 -
Development of Assist Tool for Breast Examination Using the Principle of Ultrasonic Sensor
|
||
Recruiting |
NCT04131530 -
Automatic Evaluation of Inflammation Activity in Ulcerative Colitis Using pCLE With Artificial Intelligence
|