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Title:

Development of a Machine Learning-Based Model to Predict Timed-Up-and-Go Test in Older Adults

Document type:
Zeitschriftenaufsatz
Author(s):
Kraus, Moritz; Stumpf, Ulla Cordula; Keppler, Alexander Martin; Neuerburg, Carl; Böcker, Wolfgang; Wackerhage, Henning; Baumbach, Sebastian Felix; Saller, Maximilian Michael
Abstract:
Introduction: The measurement of physical frailty in elderly patients with orthopedic impairments remains a challenge due to its subjectivity, unreliability, time-consuming nature, and limited applicability to uninjured individuals. Our study aims to address this gap by developing objective, multifactorial machine models that do not rely on mobility data and subsequently validating their predictive capacity concerning the Timed-up-and-Go test (TUG test) in orthogeriatric patients. Methods: We ut...     »
Dewey Decimal Classification:
610 Medizin und Gesundheit
Journal title:
Geriatrics
Year:
2023
Journal volume:
8
Year / month:
2023-10
Quarter:
4. Quartal
Month:
Oct
Journal issue:
5
Pages contribution:
99
Covered by:
Web of Science
Reviewed:
ja
Language:
en
Fulltext / DOI:
doi:10.3390/geriatrics8050099
Publisher:
MDPI AG
E-ISSN:
2308-3417
Impact Factor:
2,3
Scimago Quartil:
Q2
Notes:
SCImago Journal &  Country Rank
Status:
Erstveröffentlichung
Date of publication:
07.10.2023
Semester:
WS 23-24
TUM Institution:
Sportbiologie
Format:
Bild/Text
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