A diagnostic accuracy study on Artificial intelligence EEG analysis system assisted doctors to diagnose pediatric epilepsy.
Age < 18 years old
Children with suspected epilepsy
During EEG monitoring, the patients had other serious neurological diseases and mental diseases concurrently
Used medication that affect EEG data within 3 weeks, such as sedatives and anti-epileptic medications
Substandard data quality, such as data lack of key records, electrode connection discontinuity, insufficient recording time, or the presence of serious artifacts
Incomplete or missing data
children aged \< 18 years old with suspected epilepsy who need EEG examination
Cohort
Prospective
AI EEG analysis system
Diagnostic testThe first stage, physicians independently diagnose pediatric epilepsy with EEG; the second stage, Artificial intelligence EEG analysis system assisted physicians to diagnose pediatric epilepsy
To evaluate the coincidence rate between doctors' independent diagnosis and the diagnosis recommended by the AI system.
The reference standard is the EGG interpreted by 3 clinicians who had attended the uniformly training program and had more than 5 years of experience in diagnosing epilepsy in children.
To evaluate the diagnostic efficiency of clinicians at two-stage
The time taken by physicians to interpret EEG independently and with the aid of AI was measured.
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