@inproceedings{0b6aa341d95f404599ee94282fd7f6b9,
title = "Evaluating Effects of Resting-State Electroencephalography Data Pre-Processing on a Machine Learning Task for Parkinson's Disease",
abstract = "Resting-state electroencephalography pre-processing methods in machine learning studies into Parkinson's disease classification vary widely. Here three separate data sets were pre-processed to four different stages to investigate the effects on evaluation metrics, using power features from six regions-of-interest, Random Forest Classifiers for feature selection, and Support Vector Machines for classification. This showed muscle artefact inflated evaluation metrics, and alpha and theta band features produced the best results when fully pre-processing data.",
keywords = "diagnosis, electroencephalography, machine learning, Parkinson's disease, pre-processing",
author = "Robin Vlieger and Elena Daskalaki and Deborah Apthorp and Lueck, {Christian J.} and Hanna Suominen",
note = "Publisher Copyright: {\textcopyright} 2024 International Medical Informatics Association (IMIA) and IOS Press.; 19th World Congress on Medical and Health Informatics, MedInfo 2023 ; Conference date: 08-07-2023 Through 12-07-2023",
year = "2024",
month = jan,
day = "25",
doi = "10.3233/SHTI231254",
language = "English",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press BV",
pages = "1480--1481",
editor = "Jen Bichel-Findlay and Paula Otero and Philip Scott and Elaine Huesing",
booktitle = "MEDINFO 2023 - The Future is Accessible",
address = "Netherlands",
}