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Dean R Freestone

Showing results (61-70 of 76) with videos related to

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Epilepsy & Behavior : E&B|June 8, 2024
User experience of a seizure risk forecasting app: A mixed methods investigationRachel E Stirling, Ewan S Nurse, Daniel Payne, et al.
Frontiers in Neurology|August 2, 2021
Forecasting Seizure Likelihood With Wearable TechnologyRachel E Stirling, David B Grayden, Wendyl D'Souza, et al.
Frontiers in Neurology|August 23, 2021
Epileptic Seizure Cycles: Six Common Clinical MisconceptionsPhilippa J Karoly, Dean R Freestone, Dominique Eden, et al.
Epilepsia|April 8, 2022
Ambient air pollution and epileptic seizures: A panel study in AustraliaZhuying Chen, Wenhua Yu, Rongbin Xu, et al.
Epilepsia|March 29, 2020
Forecasting cycles of seizure likelihoodPhilippa J Karoly, Mark J Cook, Matias Maturana, et al.
Epilepsia|April 8, 2022
Seizure forecasting using minimally invasive, ultra-long-term subcutaneous electroencephalography: Individualized intrapatient modelsPedro F Viana, Tal Pal Attia, Mona Nasseri, et al.
Ebiomedicine|October 14, 2021
Multiday cycles of heart rate are associated with seizure likelihood: An observational cohort studyPhilippa J Karoly, Rachel E Stirling, Dean R Freestone, et al.
Nature Neuroscience|November 29, 2018
Loss of neuronal network resilience precedes seizures and determines the ictogenic nature of interictal synaptic perturbationsWei-Chih Chang, Jan Kudlacek, Jaroslav Hlinka, et al.
Epilepsia|April 20, 2022
Seizure forecasting using minimally invasive, ultra-long-term subcutaneous EEG: Generalizable cross-patient modelsTal Pal Attia, Pedro F Viana, Mona Nasseri, et al.
Eclinicalmedicine|August 13, 2021
Seizure likelihood varies with day-to-day variations in sleep duration in patients with refractory focal epilepsy: A longitudinal electroencephalography investigationKatrina L Dell, Daniel E Payne, Vaclav Kremen, et al.
Pageof 8

Showing results (61-70 of 76) with videos related to

Sort By:
Pageof 8
Epilepsy & Behavior : E&B|June 8, 2024
User experience of a seizure risk forecasting app: A mixed methods investigationRachel E Stirling, Ewan S Nurse, Daniel Payne, et al.
Frontiers in Neurology|August 2, 2021
Forecasting Seizure Likelihood With Wearable TechnologyRachel E Stirling, David B Grayden, Wendyl D'Souza, et al.
Frontiers in Neurology|August 23, 2021
Epileptic Seizure Cycles: Six Common Clinical MisconceptionsPhilippa J Karoly, Dean R Freestone, Dominique Eden, et al.
Epilepsia|April 8, 2022
Ambient air pollution and epileptic seizures: A panel study in AustraliaZhuying Chen, Wenhua Yu, Rongbin Xu, et al.
Epilepsia|March 29, 2020
Forecasting cycles of seizure likelihoodPhilippa J Karoly, Mark J Cook, Matias Maturana, et al.
Epilepsia|April 8, 2022
Seizure forecasting using minimally invasive, ultra-long-term subcutaneous electroencephalography: Individualized intrapatient modelsPedro F Viana, Tal Pal Attia, Mona Nasseri, et al.
Ebiomedicine|October 14, 2021
Multiday cycles of heart rate are associated with seizure likelihood: An observational cohort studyPhilippa J Karoly, Rachel E Stirling, Dean R Freestone, et al.
Nature Neuroscience|November 29, 2018
Loss of neuronal network resilience precedes seizures and determines the ictogenic nature of interictal synaptic perturbationsWei-Chih Chang, Jan Kudlacek, Jaroslav Hlinka, et al.
Epilepsia|April 20, 2022
Seizure forecasting using minimally invasive, ultra-long-term subcutaneous EEG: Generalizable cross-patient modelsTal Pal Attia, Pedro F Viana, Mona Nasseri, et al.
Eclinicalmedicine|August 13, 2021
Seizure likelihood varies with day-to-day variations in sleep duration in patients with refractory focal epilepsy: A longitudinal electroencephalography investigationKatrina L Dell, Daniel E Payne, Vaclav Kremen, et al.
Pageof 8