Benutzer: Gast  Login
Titel:

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

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
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 Dezimalklassifikation:
610 Medizin und Gesundheit
Zeitschriftentitel:
Geriatrics
Jahr:
2023
Band / Volume:
8
Jahr / Monat:
2023-10
Quartal:
4. Quartal
Monat:
Oct
Heft / Issue:
5
Seitenangaben Beitrag:
99
Nachgewiesen in:
Web of Science
Reviewed:
ja
Sprache:
en
Volltext / DOI:
doi:10.3390/geriatrics8050099
Verlag / Institution:
MDPI AG
E-ISSN:
2308-3417
Impact Factor:
2,3
Scimago-Quartil:
Q2
Hinweise:
SCImago Journal &  Country Rank
Status:
Erstveröffentlichung
Publikationsdatum:
07.10.2023
Semester:
WS 23-24
TUM Einrichtung:
Sportbiologie
Format:
Bild/Text
 BibTeX