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neuroreha 2025; 17(02): 70-76
DOI: 10.1055/a-2566-2243
Schwerpunkt

Computational Neurorehabilitation

Thomas Weikert
,
Elisa Du
,
Giuseppe Missale
,
Tim Unger
,
Chris Easthope Awai
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Jeder Patient in der Neurorehabilitation ist einzigartig, und jede Behandlung muss auf den Patienten zugeschnitten sein. Dieser Akt der Personalisierung wird empirisch jeden Tag zigfach durchgeführt, jedoch gibt es hierfür keine explizite Datengrundlage. Eine Möglichkeit, um der Vielfalt der Patientenbilder gerecht zu werden, besteht darin, sich in Zukunft von populationsbasierten statistischen Modellen zu verabschieden. Eine Alternative sind sogenannte N-of-1 Trials, in denen Daten von einzelnen Patienten und ihren Therapieverläufen gesammelt und Metaanalysen über den Behandlungserfolg durchgeführt werden. Durch maschinelles Lernen werden in großen Datensätzen Repräsentationsräume und Trajektorien identifiziert, die als digitale klinische Entscheidungshilfe fungieren können. Hierfür müssen jedoch intelligente Datenerfassungssysteme im klinischen Alltag Einzug finden, um eine ausreichende Datendichte zu erzielen. Der Artikel stellt ein solches Datenerfassungssystem vor und beschreibt die Erfahrungen einer Implementierung in einer Schlaganfall-Rehaklinik.



Publication History

Article published online:
05 June 2025

© 2025. Thieme. All rights reserved.

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