Основные понятия
The author explores the advancements in deep learning and computer vision techniques for analyzing seizure videos, aiming to enhance medical decision-making and patient care through quantitative evidence and decision support.
Аннотация
The content delves into the utilization of deep learning and computer vision in analyzing seizure videos to improve accuracy in detection, classification, and prediction. It highlights the benefits of behavior monitoring tools in providing objective information and reducing documentation efforts. The review discusses various approaches, challenges, and future research directions in the field of seizure video analysis.
Статистика
"Historically, these approaches have been used for disease detection, classification, and prediction using diagnostic data."
"Behavior monitoring tools offer several advantages such as providing objective information, detecting challenging-to-observe events, reducing documentation efforts."
"The main applications could be improved seizure detection methods; refined semiology analysis for predicting seizure type and cerebral localization."
Цитаты
"Nocturnal convulsive seizures by combining hand-crafted features from video and EEG signals." - Aghaei et al.
"Exploiting optical flow calculations and the reconstruction vector field to detect Rolandic Epilepsy." - Wu et al.