CompletedNot Applicable

Artificial Intelligence-based Video Analysis to Detect Infantile Spasms

United States61 participantsStarted 2024-08-26

Plain-language summary

Infantile spasms are a type of seizure linked to developmental issues. Unfortunately, they are often misdiagnosed, causing delays in treatment. The purpose of this study is to develop a computer program that can reliably differentiate infantile spasms from similar, yet benign movements in videos. This computer program will learn from videos taken by parents of study participants. Quickly recognizing and treating infantile spasms is crucial for ensuring the best developmental outcomes.

Who can participate

Age range2 Years

SexALL

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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.

Inclusion Criteria: * Participant age less than 24 months * Participant evaluated in the Johns Hopkins Outpatient Center, Johns Hopkins Pediatric Emergency Department or Johns Hopkins Inpatient Units due to spells of abnormal movement or seizure * Participant evaluated by a pediatric neurologist during the outpatient or inpatient visit at Johns Hopkins Hospital * At least one video recording of the spell of abnormal movement produced by the parent/guardian available for provider review Exclusion Criteria: * Poor video recording quality * Entire patient is not in frame

What they're measuring

Model Sensitivity (Recall)

Timeframe: 2 years

Model Specificity

Timeframe: 2 years

Model Positive Predictive Value (Precision)

Timeframe: 2 years

Model Negative Predictive Value

Timeframe: 2 years

Trial details

NCT IDNCT06315829

SponsorJohns Hopkins University

Sponsor typeOTHER

Study typeOBSERVATIONAL

Primary completion2026-05-06

View on ClinicalTrials.gov More Infantile Spasms trials