Automatic detection of abnormal EEG signals using wavelet feature extraction and gradient boosting decision tree

Computer Science

• Pattern Classification 100%
• Diagnostics 100%
• Decision Tree 100%
• Extracted Feature 100%
• Binary Classification 100%
• Classification Framework 100%
• Classification 50%
• Workload 50%
• Classification (Machine Learning) 50%
• Feature Space 50%
• Statistical Feature 50%
• Automatic Detection 50%
• Related Disorder 50%
• Classification Accuracy 50%
• Decision Tree Classifier 50%

Medicine and Dentistry

• Electroencephalogram 100%
• Diseases 14%
• Final Diagnosis 14%