- Lectures / Webinars
- Responsible AI in paediatric neurology; smartphone video and clinical metadata facilitating rapid diagnosis & treatment
Responsible AI in paediatric neurology; smartphone video and clinical metadata facilitating rapid diagnosis & treatment
New
This content is only available for our subscribers. Please click here to subscribe to a subscription plan for unrestricted access.
ICNC2024
Symposia: Big Data, Artificial Intelligence and Machine Learning In The Diagnosis and Management of Epilepsy
Responsible AI in paediatric neurology; smartphone video and clinical metadata facilitating rapid diagnosis & treatment
Sameer Zuberi
Deep learning models for detection of epileptic seizures spatiotemporally from video may develop from the interface of fundamental computer vision, human motion analysis, machine learning research and interdisciplinary working between clinicians and data scientists. Early research has primarily used highly controlled video in epilepsy monitoring units or using multiple cameras. Research focusing on analysis of uncontrolled carer recorded smartphone video will be challenging but has the prospect of leveraging data from 6.9 billion smartphones and more accurately reflecting community needs/clinical resources worldwide. Integrating a research programme through a national ethical framework has allowed our team to develop a neurology video research database from a clinical platform vCreate Neuro (www.vcreate.tv/neuro). The application has > 27k videos and is growing by > 800/month. Established in >70 services, projects are being established in high and restricted resource settings in Europe, N America, Asia, Australasia, the Pacific, and Africa. Videos are uploaded to a secure web-based platform with associated metadata and classified by clinicians, facilitating a curated clinical and research database. We will discuss the concepts of responsible AI as applied to video of children, research methodologies including annotation, 2D & 3D skeletal pose sequences and how an AI algorithm can be integrated into a diagnostic and management pathway and adapted to local models of healthcare
Other Lectures in this symposium
Artificial Intelligence in the diagnosis of epilepsy in resource poor areas.
Generative models of brain dynamics in epilepsy
Multicentre Epilepsy Lesion Detection project: bringing AI into epilepsy presurgical planning
Machine Learning to improve diagnosis of epilepsy in infancy and potential solution for remote detection.