@inproceedings{9d98b6447c6649fa9118ef42be2e0449,
title = "The Use of Event-Related Potentials and Machine Learning to Improve Diagnostic Testing and Prediction of Disease Progression in Parkinson's Disease",
abstract = "Current tests of disease status in Parkinson's disease suffer from high variability, limiting their ability to determine disease severity and prognosis. Event-related potentials, in conjunction with machine learning, may provide a more objective assessment. In this study, we will use event-related potentials to develop machine learning models, aiming to provide an objective way to assess disease status and predict disease progression in Parkinson's disease.",
keywords = "Diagnosis, Parkinson disease, disease status, event-related potentials, machine learning, prediction",
author = "Robin Vlieger and Elena Daskalaki and Deborah Apthorp and Lueck, {Christian J.} and Hanna Suominen",
note = "Publisher Copyright: {\textcopyright} 2021 International Medical Informatics Association (IMIA) and IOS Press.; 15th International Congress in Nursing Informatics: Nurses and Midwives in the Digital Age, NI 2021 ; Conference date: 23-08-2021 Through 02-09-2021",
year = "2021",
month = dec,
day = "15",
doi = "10.3233/SHTI210737",
language = "English",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press BV",
pages = "333--335",
editor = "Michelle Honey and Charlene Ronquillo and Ting-Ting Lee and Lucy Westbrooke",
booktitle = "Nurses and Midwives in the Digital Age - Selected Papers, Posters and Panels from the 15th International Congress in Nursing Informatics",
address = "Netherlands",
}