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Crowdsourced Algorithms Predict Epileptic Seizures

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Crowdsourcing of more than 10,000 algorithms worldwide has enabled Melbourne researchers to predict clinically relevant epileptic seizures in a wider range of patients than previously possible.

In 2016 the researchers ran a seizure prediction challenge on the online data science platform kaggle.com. The contest focused on seizure prediction from long-term electrical brain activity recordings obtained in 2013 from a clinical trial of NeuroVista’s implantable Seizure Advisory System. Almost 478 teams developed 10,000 algorithms, and the top algorithms were tested on the patients with the lowest seizure prediction performance based on previous studies.

The results have now been published in Brain (https://goo.gl/DxbX9e). “Our evaluation revealed on average a 90% improvement in seizure prediction performance, compared to previous results,” said Dr Levin Kuhlmann from the University of Melbourne’s Graeme Clarke Institute and St Vincent’s Hospital.

“Epilepsy is highly different among individuals,” Kuhlmann explained. “Results showed different algorithms performed best for different patients, supporting the use of patient-specific algorithms and long-term monitoring.”

The researchers have now developed the online platform epilepsyecosystem.org for algorithm and data sharing to further...

The full text of this article can be purchased from Informit.