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SVP Detection Using Machine Learning

NCT05731765 · Status: ACTIVE_NOT_RECRUITING · Type: OBSERVATIONAL · Enrollment: 210

Last updated 2024-03-06

No results posted yet for this study

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

  • Intracranial Pressure Increase

Interventions

DIAGNOSTIC_TEST

Machine Learning Model

Automated machine learning system for the detection of spontaneous venous pulsations and quantification of intracranial pressure

Sponsors & Collaborators

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2023-03-01
Primary Completion
2024-11-30
Completion
2024-11-30

Countries

  • United Kingdom

Study Locations

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Entities

Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05731765 on ClinicalTrials.gov