Trials / Unknown
UnknownNCT05731765
SVP Detection Using Machine Learning
Automated Detection of Spontaneous Venous Pulsations Within Fundal Videos Using Machine Learning
- Status
- Unknown
- Phase
- —
- Study type
- Observational
- Enrollment
- 210 (estimated)
- Sponsor
- King's College London · Academic / Other
- Sex
- All
- Age
- 18 Years
- Healthy volunteers
- Accepted
Summary
This diagnostic study will use 410 retrospectively captured fundal videos to develop ML systems that detect SVPs and quantify ICP. The ground truth will be generated from the annotations of two independent, masked clinicians, with arbitration by an ophthalmology consultant in cases of disagreement.
Conditions
Interventions
| Type | Name | Description |
|---|---|---|
| DIAGNOSTIC_TEST | Machine Learning Model | Automated machine learning system for the detection of spontaneous venous pulsations and quantification of intracranial pressure |
Timeline
- Start date
- 2023-03-01
- Primary completion
- 2024-11-01
- Completion
- 2024-11-01
- First posted
- 2023-02-16
- Last updated
- 2024-03-06
Locations
1 site across 1 country: United Kingdom
Source: ClinicalTrials.gov record NCT05731765. Inclusion in this directory is not an endorsement.