- Lectures / Webinars
- Machine Learning to improve diagnosis of epilepsy in infancy and potential solution for remote detection.
Machine Learning to improve diagnosis of epilepsy in infancy and potential solution for remote detection.
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ICNC2024
Symposia: Big Data, Artificial Intelligence and Machine Learning In The Diagnosis and Management of Epilepsy
Machine Learning to improve diagnosis of epilepsy in infancy and potential solution for remote detection.
Jay Shetty
Epilepsy has bimodal age distribution with peak incidence in young children and older adults. Amongst young children incidence is common in infancy and has worse neurodevelopmental outcome compared to other age groups. This is due to multiple factors including etiology, epileptic encephalopathy, and limited treatment availability. Diagnosis can often be delayed as the seizure semiology are different and may mimic normal behaviour in infants. EEG is a useful tool for confirming diagnosis and monitor treatment at this age group.
Timely EEG availability is variable across the world. Expertise in interpreting infant EEGs is limited. We will discuss our early work on use of AI to detect EEG abnormalities using existing large dataset. This work is an early step to design a remote detection and monitoring.
Other Lectures in this symposium:
Multicentre Epilepsy Lesion Detection project: bringing AI into epilepsy presurgical planning
Generative models of brain dynamics in epilepsy
Artificial Intelligence in the diagnosis of epilepsy in resource poor areas.