O2 Muu julkaisu
The Use of Event-Related Potentials and Machine Learning to Improve Diagnostic Testing and Prediction of Disease Progression in Parkinson's Disease
Tekijät: Vlieger Robin, Daskalaki Elena, Apthorp Deborah, Lueck Christian J, Suominen Hanna
Toimittaja: Michelle Honey, Charlene Ronquillo, Ting-Ting Lee, Lucy Westbrooke
Konferenssin vakiintunut nimi: International Congress in Nursing Informatics
Julkaisuvuosi: 2021
Journal: Studies in Health Technology and Informatics
Kokoomateoksen nimi: Nurses and Midwives in the Digital Age: Selected Papers, Posters and Panels from the 15th International Congress in Nursing Informatics
Tietokannassa oleva lehden nimi: Studies in health technology and informatics
Lehden akronyymi: Stud Health Technol Inform
Sarjan nimi: Studies in Health Technology and Informatics
Vuosikerta: 284
Aloitussivu: 333
Lopetussivu: 335
ISSN: 0926-9630
eISSN: 1879-8365
DOI: https://doi.org/10.3233/SHTI210737
Verkko-osoite: https://ebooks.iospress.nl/doi/10.3233/SHTI210737
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/176265723
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.
Ladattava julkaisu This is an electronic reprint of the original article. |  |
