The Use of Event-Related Potentials and Machine Learning to Improve Diagnostic Testing and Prediction of Disease Progression in Parkinson's Disease

Robin Vlieger; Elena Daskalaki; Deborah Apthorp; Christian J Lueck; Hanna Suominen

doi:10.3233/SHTI210737

The Use of Event-Related Potentials and Machine Learning to Improve Diagnostic Testing and Prediction of Disease Progression in Parkinson's Disease

Robin Vlieger, Elena Daskalaki, Deborah Apthorp, Christian J Lueck, Hanna Suominen

School of Psychology

Research output: Contribution to conference › Abstract › peer-review

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.

Original language	English
Pages	333-335
DOIs	https://doi.org/10.3233/SHTI210737
Publication status	Published - 2021
Event	NI 2021: 15th International Congress in Nursing Informatics - Online Event, Online Event Duration: 23 Aug 2021 → 2 Sept 2021

Conference

Conference	NI 2021: 15th International Congress in Nursing Informatics
City	Online Event
Period	23/08/21 → 2/09/21

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10.3233/SHTI210737

https://hdl.handle.net/1959.11/52936Licence: CC BY-NC

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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.",

author = "Robin Vlieger and Elena Daskalaki and Deborah Apthorp and Lueck, \{Christian J\} and Hanna Suominen",

year = "2021",

doi = "10.3233/SHTI210737",

language = "English",

pages = "333--335",

note = "NI 2021: 15th International Congress in Nursing Informatics ; Conference date: 23-08-2021 Through 02-09-2021",

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The Use of Event-Related Potentials and Machine Learning to Improve Diagnostic Testing and Prediction of Disease Progression in Parkinson's Disease. / Vlieger, Robin; Daskalaki, Elena; Apthorp, Deborah et al.
2021. 333-335 Abstract from NI 2021: 15th International Congress in Nursing Informatics, Online Event.

Research output: Contribution to conference › Abstract › peer-review

TY - CONF

T1 - The Use of Event-Related Potentials and Machine Learning to Improve Diagnostic Testing and Prediction of Disease Progression in Parkinson's Disease

AU - Vlieger, Robin

AU - Daskalaki, Elena

AU - Apthorp, Deborah

AU - Lueck, Christian J

AU - Suominen, Hanna

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/85122043820

U2 - 10.3233/SHTI210737

DO - 10.3233/SHTI210737

M3 - Abstract

C2 - 34920540

SP - 333

EP - 335

T2 - NI 2021: 15th International Congress in Nursing Informatics

Y2 - 23 August 2021 through 2 September 2021

ER -

The Use of Event-Related Potentials and Machine Learning to Improve Diagnostic Testing and Prediction of Disease Progression in Parkinson's Disease

Abstract

Conference

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