Multi-center validation study of automated classification of pathological slowing in adult scalp electroencephalograms via frequency features

• المؤلفون الرئيسيون: Peh, Wei Yan, Thomas, John, Bagheri, Elham, Chaudhari, Rima, Karia, Sagar, Rathakrishnan, Rahul, Saini, Vinay, Shah, Nilesh, Srivastava, Rohit, Tan, Yee-Leng, Dauwels, Justin
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2022
• الموضوعات: Engineering::Electrical and electronic engineering; Electroencephalogram; EEG Slowing
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/159814

Pathological slowing in the electroencephalogram (EEG) is widely investigated for the diagnosis of neurological disorders. Currently, the gold standard for slowing detection is the visual inspection of the EEG by experts, which is time-consuming and subjective. To address those issues, we propose th...