ArticleNPJ digital medicine2025
Detection of epileptic spasms using foundational AI and smartphone videos.
Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Artificial intelligence-assisted detection of epileptic spasms using electroencephalographic-video analysis.Epilepsia · 2026Article
- Towards generalizable seizure monitoring: EpiVLM for cross-environment detection and classification.NPJ digital medicine · 2026Article
- Smart assistive technologies for neurodisorders: A review on AI, IoT, and wearable systems for enhanced patient care.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Review
- Implementation of a digital health tool for seizure video transfer in a pediatric epilepsy center: A prospective pilot study.Epilepsy & behavior reports · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Infantile epileptic spasm syndrome (IESS) is a severe neurological disorder characterized by epileptic spasms (ES). Timely diagnosis is crucial, but it is often delayed due to symptom misidentification. Smartphone videos can aid in diagnosis, but the availability of specialist review is limited. We fine-tuned a foundational video model for ES detection using social media videos, thus addressing this clinical need and the challenge of data scarcity in rare disorders. Our model, trained on 141 children with 991 ES and 127 children without seizures, achieved high performance (area under the receiver-operating-characteristic curve (AUC) 0.96, 82% sensitivity, 90% specificity) including validation on external datasets from social media derived smartphone videos (93 children, 70 seizures, AUC 0.98, false alarm rate (FAR) 0.75%) and gold-standard video-EEG (22 children, 45 seizures, AUC 0.98, FAR 3.4%). We demonstrate the potential of smartphone videos for AI-powered analysis as the basis for accelerated IESS diagnosis and a novel strategy for the diagnosis of rare disorders.
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Registered trials
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