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Clinical Validation of DystoniaNet Deep Learning Platform for Diagnosis of Isolated Dystonia

NCT05317390 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 1000

Last updated 2025-12-02

No results posted yet for this study

Summary

This research involves retrospective and prospective studies for clinical validation of a DystoniaNet deep learning platform for the diagnosis of isolated dystonia.

Conditions

  • Dystonia
  • Drug Induced Dystonia
  • Parkinson Disease
  • Essential Tremor
  • Dyskinesias
  • Myoclonus
  • Tic Disorders
  • Torticollis
  • Ulnar Nerve Entrapment
  • Temporomandibular Joint Disorders
  • Dysphonia

Interventions

DIAGNOSTIC_TEST

DystoniaNet-based diagnosis of isolated dystonia

DystoniaNet will be used for the diagnosis of dystonia and its differential diagnosis from other neurological and non-neurological disorders mimicking symptoms of dystonia

Sponsors & Collaborators

  • Massachusetts Eye and Ear Infirmary

    lead OTHER

Principal Investigators

  • Kristina Simonyan, MD, PhD · Massachusetts Eye and Ear

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
DOUBLE
Model
PARALLEL

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2022-06-01
Primary Completion
2028-04-30
Completion
2028-04-30

Countries

  • United States

Study Locations

More Related Trials

Entities

Diseases

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 NCT05317390 on ClinicalTrials.gov