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Development and establishment of an artificial intelligence–assisted system for the diagnosis and classification of pediatric epilepsy based on seizure video recordings

Development and establishment of an artificial intelligence–assisted system for the diagnosis and classification of pediatric epilepsy based on seizure video recordings

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600116177
Enrollment
Unknown
Registered
2026-01-06
Start date
2026-01-06
Completion date
Unknown
Last updated
2026-01-12

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Epilepsy

Interventions

Model construction set:None

Sponsors

Beijing Childrens Hospital,Capital Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
No minimum to 18 Years

Inclusion criteria

Inclusion criteria: Ages 2 months to 18 years; undergoing video electroencephalography (EEG) due to episodic events; episodic events are recorded during video EEG monitoring, and the duration of the events does not exceed 5 minutes; experts have reviewed the video EEG data and are in complete agreement on disease diagnosis and interpretation; has signed the informed consent form and is willing to participate in this study.

Exclusion criteria

Exclusion criteria: 1.The child in the video is severely occluded, making it impossible to extract facial or body behavioral information; 2.The paroxysmal event cannot be clearly classified as epileptic or non-epileptic after clinical evaluation.

Design outcomes

Primary

MeasureTime frame
Performance of the deep learning model;

Countries

China

Contacts

Public ContactTinghong Liu

Beijing Childrens Hospital,Capital Medical University

liutinghong1@163.com+86 10 5961 6785

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026