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NCT04738552

A Study of Detection of Paroxysmal Events Utilizing Computer Vision and Machine Learning

Completed Last updated 25 November 2024
What this trial tests

trial testing Nelli in Epilepsy in 233 participants. Completed in 27 November 2022.

Timeline
9 January 2020
Primary endpoint
27 November 2022
27 November 2022

Quick facts

Lead sponsorNeuro Event Labs Inc.
StatusCompleted
Study typeOBSERVATIONAL
Enrollment233
Start date9 January 2020
Primary completion27 November 2022
Estimated completion27 November 2022
Sites1 location across United States

Drugs / interventions tested

Conditions studied

Sponsor

Neuro Event Labs Inc.

Who can join

Adults 18 to 99, any sex, with Epilepsy. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

Increased computational power has made it possible to implement complex image recognition tasks and machine learning to be implemented in every day usage. The computer vision and machine learning based solution used in this project (Nelli) is an automatic seizure detection and reporting method that has a CE mark for this specific use. The present study will provide data to expand the utility and detection capability of NELLI and enhance the accuracy and clinical utility of automated computer vision and machine learning based seizure detection.

Publications & conference data

No peer-reviewed publications indexed yet for this trial. Completed trials usually publish results within 12-18 months.

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Other trials of Nelli

Trials testing the same drug.

Other recruiting trials for Epilepsy

Currently open trials in the same condition.

Other Neuro Event Labs Inc. trials

Trials by the same sponsor.

Verify against primary sources

Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT04738552.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing