https://www.epilepsyecosystem.org/
Epilepsyecosystem.org is a crowd-sourcing ecosystem for
improving the performance of seizure prediction algorithms in order to
make seizure prediction a viable treatment option for those suffering
from epilepsy.
Epilepsy afflicts nearly 1% of the world's
population, and is characterized by the occurrence of spontaneous
seizures. For many patients, anticonvulsant medications can be given at
sufficiently high doses to prevent seizures, but patients frequently
suffer side effects. For 20-40% of patients with epilepsy, medications
are not effective. Even after surgical removal of epilepsy, many
patients continue to experience spontaneous seizures. Despite the fact
that seizures occur infrequently, patients with epilepsy experience
persistent anxiety due to the possibility of a seizure occurring.
Seizure
forecasting systems have the potential to help patients with epilepsy
lead more normal lives. In order for electrical brain activity (EEG)
based seizure forecasting systems to work effectively, computational
algorithms must reliably identify periods of increased probability of
seizure occurrence. If these seizure-permissive brain states can be
identified, devices designed to warn patients of impeding seizures would
be possible. Patients could avoid potentially dangerous activities like
driving or swimming, and medications could be administered only when
needed to prevent impending seizures, reducing overall side effects.
A Crowd-Sourcing Ecosystem for Seizure Prediction
Epilepsyecosystem.org is the evolution of a Crowd-Sourcing Ecosystem for Seizure Prediction that began with the ‘Melbourne-University AES-MathWorks-NIH Seizure Prediction Challenge’
that was hosted on Kaggle.com in 2016. The contest focused on seizure
prediction using long-term electrical brain activity recordings from
humans obtained from the world-first clinical trial of the implantable
NeuroVista Seizure Advisory System. Over 10,000 algorithms were
submitted. The top algorithms from the contest were evaluated on
additional held out data and demonstrated improvements in seizure
prediction performance relative to the original trial results.
Epilepsyecosystem.org offers the opportunity to yield further
improvements with the contest dataset. The top algorithms in the
ecosystem will be invited for evaluation on the full clinical trial
database, a one-of-a-kind world-class dataset, with the aim of finding
the best algorithms for the widest range of patients.
Acknowledgments
Epilepsyecosystem.org
is supported by the Aikenhead Centre for Medical Discovery at St.
Vincent’s Hospital Melbourne, the University of Melbourne, Swinburne
University of Technology and Seer Medical.
References
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