An Automated Methodology for Epileptic Seizure Detection Using Random Forest Classifier

N. Samreen Fathima; M. K. Mariam Bee; Abhishek Bhattacharya; Soumi Dutta

doi:10.1007/978-981-33-4367-2_70

ScienceGate Book Chapters

BOOK-CHAPTER

An Automated Methodology for Epileptic Seizure Detection Using Random Forest Classifier

N. Samreen Fathima M. K. Mariam Bee Abhishek Bhattacharya Soumi Dutta

Year: 2021 Advances in intelligent systems and computing Pages: 735-744 Publisher: Springer Nature

DOI: 10.1007/978-981-33-4367-2_70

Get Full-Text PDF Get Analytical Report

Keywords:

Electroencephalography Epilepsy Scalp Pattern recognition (psychology) Random forest Epileptic seizure Artificial intelligence Computer science Standard deviation Brain activity and meditation Psychology Neuroscience Medicine Mathematics Statistics

Metrics

Cited By

0.84

FWCI (Field Weighted Citation Impact)

Refs

0.74

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

EEG and Brain-Computer Interfaces

Life Sciences → Neuroscience → Cognitive Neuroscience

Blind Source Separation Techniques

Physical Sciences → Computer Science → Signal Processing

Currency Recognition and Detection

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

An Automated Methodology for Epileptic Seizure Detection Using Random Forest Classifier

Metrics

Citation History

Topics

Related Documents

Automated epileptic seizure detection using improved correlation-based feature selection with random forest classifier

An Improved Optimization Algorithm for Epileptic Seizure Detection in EEG Signals Using Random Forest Classifier

Epileptic Seizure Detection using Variational Quantum Classifier

Epileptic Seizure Detection Using Quantum Support Vector Classifier

Classification of Seizure Types Using Random Forest Classifier