Project ID iCASE2024_02_NS-MH


Co Supervisor 1A Institute of Psychiatry, Psychology & Neuroscience, School of Mental Health & Psychological Sciences, Department of PsychologyWebsite

Co Supervisor 1B Faculty of Life Sciences & Medicine, School of Life Course & Population Sciences, Department of Women & Children’s HealthWebsite

Additional Supervisor Dr Ben Moore & Prof Sameer Zuberi

Partner vCreate Neuro

Predictors of neurodevelopmental outcomes in early-onset epilepsy: leveraging AI in video-based and electronic health records (BEE-HIVES)

Early-onset epilepsy is associated with poor developmental outcomes. Limited evidence suggests that specific maternal characteristics are associated with early-onset epilepsy, and that certain features of epilepsy predict diagnosis of neurodevelopmental conditions, including autism. The Brain development in Early Epilepsy (BEE) Study aims to define neurocognitive markers that predict emerging developmental difficulties in infants with epilepsy using prospective longitudinal measurement ( The BEE Study collaborates with the Early Life Cross Linkage in Research (eLIXIR) research registry that provides a continuous prospective link between maternal, neonatal and primary care data of mothers and children. The proposed partner, vCreate Neuro, have developed an innovative secure platform for patients/carers to share smartphone-recorded videos of seizures for remote clinical management. Planned initiatives to integrate developmental assessment create a unique opportunity to systematically chart children’s behaviour and development, to provide objective markers for early phase clinical trials.

This PhD will combine advances in artificial intelligence with linkage of routine medical records and prospective measurement of neurodevelopmental difficulties in early-onset epilepsy. The student will first test the acceptability of the protocol by consulting with the epilepsy community, before applying machine learning algorithms to the extensive vCreate Neuro video database to assess development and behaviour. Secondly, the feasibility of linking coded videos to eLIXIR will be established, and associations between maternal factors and development will be characterised. Thirdly, the student will identify potential predictors of neurodevelopmental difficulties in early-onset epilepsy using sophisticated analysis of longitudinal data.

Multiple integrated secondments with vCreate Neuro provide structured support with large-scale remote data collection and digital technologies, combined with interdisciplinary training on early developmental assessment, machine learning approaches to video coding and statistical analysis at King’s. The student will work with experts in various company roles alongside clinical teams and charities to enhance communication skills and provide a unique and diverse skillset

Third Supervisor: Dr Nicholas Cummins

Representative Publications

1. Tye, C., McEwen, F., Liang, H., Underwood, L., Woodhouse, E., Barked, E.D., Sheerin, F., Higgins, N., Yates, J.R.W., TS 2000 Study Group, Bolton, P. (2020). Long-term cognitive outcomes in tuberous sclerosis complex. Developmental Medicine and Child Neurology, 62(3), 322-329. doi: 10.1111/dmcn.14356;
2. Tye, C., Bussu, G., Gliga, T., Elsabbagh, M., Pasco, G., Johnsen, K., Charman, T., Jones, E.J.H., Buitelaar, J., Johnson, M.H., & BASIS Team. (2022). Understanding the nature of face processing in early autism: A prospective study. Journal of Psychopathology and Clinical Science, 131(6), 542-555. doi: 10.1037/abn0000648;
3. Tye, C., McEwen, F., Liang, H., Underwood, L., Woodhouse, E., Barked, E.D., Sheerin, F., Higgins, N., Yates, J.R.W., TS 2000 Study Group, Bolton, P. (2023). Epilepsy severity mediates association between mutation type and ADHD symptoms in tuberous sclerosis complex. Epilepsia, 64(3), e30-e35. doi: 10.1111/epi.17507

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