Identifying seizure risk factors: A comparison of sleep, weather, and temporal features using a Bayesian forecast

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F21%3A00346889" target="_blank" >RIV/68407700:21730/21:00346889 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1111/epi.16785" target="_blank" >https://doi.org/10.1111/epi.16785</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1111/epi.16785" target="_blank" >10.1111/epi.16785</a>

Result language
angličtina
Original language name
Identifying seizure risk factors: A comparison of sleep, weather, and temporal features using a Bayesian forecast
Original language description
Most seizure forecasting algorithms have relied on features specific to electroencephalographic recordings. Environmental and physiological factors,such as weather and sleep, have long been suspected to affect brain activity and seizure occurrence but have not been fully explored as prior information for seizure forecasts in a patient-specific analysis. The study aimed to quantify whether sleep, weather, and temporal factors (time of day, day of week, and lunar phase) can provide predictive prior probabilities that may be used to improve seizure forecasts.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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