|Title:||Analyzing seasonal incidence patterns of epileptic seizure using various statistical methods||Authors:||Lin J.-N.
MATTHEW HUEI-MING MA
|Issue Date:||2016||Journal Volume:||2||Start page/Pages:||570-575||Source:||Proceedings - International Conference on Machine Learning and Cybernetics||Abstract:||
An epileptic seizure is a brief episode of symptoms due to abnormal excessive or synchronous neuronal activity in the brain. Epilepsy is a chronic disorder that affects people of all ages, and one of the most common neurological diseases globally. Epilepsy can have both genetic and acquired causes, nevertheless, the exact mechanism of epilepsy is still unknown. It merits further investigation under which circumstances the brain shifts into the epileptic condition. On the other hand, the influence of the environment on the human organism is one central problem for scientific investigation. It has been suggested previously that incidence of epileptic seizure varies significantly with the weather. Thus, based on the emergency medical service database, this study analyzed the seasonal incidence patterns of epileptic seizure in Taiwan using statistical testing methods. Moreover, various types of meteorological data have been evaluated respectively for their associations with epileptic seizure using the idea of partial correlation. ? 2016 IEEE.
|URI:||https://scholars.lib.ntu.edu.tw/handle/123456789/455744||DOI:||10.1109/ICMLC.2016.7872950||SDG/Keyword:||Brain; Emergency services; Machine learning; Meteorology; Neurodegenerative diseases; Neurophysiology; Testing; Emergency medical services; Epileptic seizures; Meteorological data; Neurological disease; Partial correlation; Scientific investigation; Seasonal incidence pattern; Statistical testing methods; Statistical methods
|Appears in Collections:||醫學院附設醫院 (臺大醫院)|
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